Overview

Dataset statistics

Number of variables88
Number of observations404571
Missing cells1425598
Missing cells (%)4.0%
Total size in memory271.6 MiB
Average record size in memory704.0 B

Variable types

Numeric75
Text13

Alerts

vlan_id has constant value ""Constant
bidirectional_cwr_packets has constant value ""Constant
bidirectional_ece_packets has constant value ""Constant
bidirectional_urg_packets has constant value ""Constant
src2dst_cwr_packets has constant value ""Constant
src2dst_ece_packets has constant value ""Constant
src2dst_urg_packets has constant value ""Constant
dst2src_cwr_packets has constant value ""Constant
dst2src_ece_packets has constant value ""Constant
dst2src_urg_packets has constant value ""Constant
label has constant value ""Constant
requested_server_name has 29634 (7.3%) missing valuesMissing
client_fingerprint has 334965 (82.8%) missing valuesMissing
server_fingerprint has 335220 (82.9%) missing valuesMissing
user_agent has 360975 (89.2%) missing valuesMissing
content_type has 364804 (90.2%) missing valuesMissing
expiration_id is highly skewed (γ1 = 59.28773098)Skewed
ip_version is highly skewed (γ1 = 29.70325545)Skewed
tunnel_id is highly skewed (γ1 = 449.759936)Skewed
bidirectional_packets is highly skewed (γ1 = 270.1217905)Skewed
bidirectional_bytes is highly skewed (γ1 = 287.838145)Skewed
src2dst_packets is highly skewed (γ1 = 383.4434809)Skewed
src2dst_bytes is highly skewed (γ1 = 417.4640014)Skewed
dst2src_packets is highly skewed (γ1 = 276.6955355)Skewed
dst2src_bytes is highly skewed (γ1 = 338.7406119)Skewed
bidirectional_min_piat_ms is highly skewed (γ1 = 107.5716106)Skewed
bidirectional_ack_packets is highly skewed (γ1 = 317.0454919)Skewed
bidirectional_psh_packets is highly skewed (γ1 = 308.397628)Skewed
bidirectional_rst_packets is highly skewed (γ1 = 59.96230729)Skewed
src2dst_ack_packets is highly skewed (γ1 = 454.7169798)Skewed
src2dst_psh_packets is highly skewed (γ1 = 255.1348783)Skewed
src2dst_rst_packets is highly skewed (γ1 = 86.02218879)Skewed
dst2src_ack_packets is highly skewed (γ1 = 317.761118)Skewed
dst2src_psh_packets is highly skewed (γ1 = 334.7878987)Skewed
dst2src_rst_packets is highly skewed (γ1 = 40.00271573)Skewed
expiration_id has 404456 (> 99.9%) zerosZeros
vlan_id has 404571 (100.0%) zerosZeros
tunnel_id has 404569 (> 99.9%) zerosZeros
src2dst_duration_ms has 249230 (61.6%) zerosZeros
dst2src_first_seen_ms has 4514 (1.1%) zerosZeros
dst2src_last_seen_ms has 4514 (1.1%) zerosZeros
dst2src_duration_ms has 241966 (59.8%) zerosZeros
dst2src_packets has 4514 (1.1%) zerosZeros
dst2src_bytes has 4514 (1.1%) zerosZeros
bidirectional_stddev_ps has 4519 (1.1%) zerosZeros
src2dst_stddev_ps has 259503 (64.1%) zerosZeros
dst2src_min_ps has 4514 (1.1%) zerosZeros
dst2src_mean_ps has 4514 (1.1%) zerosZeros
dst2src_stddev_ps has 234524 (58.0%) zerosZeros
dst2src_max_ps has 4514 (1.1%) zerosZeros
bidirectional_min_piat_ms has 149584 (37.0%) zerosZeros
bidirectional_stddev_piat_ms has 224911 (55.6%) zerosZeros
src2dst_min_piat_ms has 306451 (75.7%) zerosZeros
src2dst_mean_piat_ms has 249230 (61.6%) zerosZeros
src2dst_stddev_piat_ms has 261625 (64.7%) zerosZeros
src2dst_max_piat_ms has 249230 (61.6%) zerosZeros
dst2src_min_piat_ms has 337620 (83.5%) zerosZeros
dst2src_mean_piat_ms has 241966 (59.8%) zerosZeros
dst2src_stddev_piat_ms has 272321 (67.3%) zerosZeros
dst2src_max_piat_ms has 241966 (59.8%) zerosZeros
bidirectional_syn_packets has 264599 (65.4%) zerosZeros
bidirectional_cwr_packets has 404571 (100.0%) zerosZeros
bidirectional_ece_packets has 404571 (100.0%) zerosZeros
bidirectional_urg_packets has 404571 (100.0%) zerosZeros
bidirectional_ack_packets has 265051 (65.5%) zerosZeros
bidirectional_psh_packets has 288903 (71.4%) zerosZeros
bidirectional_rst_packets has 374384 (92.5%) zerosZeros
bidirectional_fin_packets has 268274 (66.3%) zerosZeros
src2dst_syn_packets has 264600 (65.4%) zerosZeros
src2dst_cwr_packets has 404571 (100.0%) zerosZeros
src2dst_ece_packets has 404571 (100.0%) zerosZeros
src2dst_urg_packets has 404571 (100.0%) zerosZeros
src2dst_ack_packets has 266380 (65.8%) zerosZeros
src2dst_psh_packets has 289591 (71.6%) zerosZeros
src2dst_rst_packets has 379516 (93.8%) zerosZeros
src2dst_fin_packets has 270708 (66.9%) zerosZeros
dst2src_syn_packets has 268137 (66.3%) zerosZeros
dst2src_cwr_packets has 404571 (100.0%) zerosZeros
dst2src_ece_packets has 404571 (100.0%) zerosZeros
dst2src_urg_packets has 404571 (100.0%) zerosZeros
dst2src_ack_packets has 265099 (65.5%) zerosZeros
dst2src_psh_packets has 290033 (71.7%) zerosZeros
dst2src_rst_packets has 388555 (96.0%) zerosZeros
dst2src_fin_packets has 274830 (67.9%) zerosZeros
application_is_guessed has 380188 (94.0%) zerosZeros
label has 404571 (100.0%) zerosZeros

Reproduction

Analysis started2023-06-05 18:09:06.467520
Analysis finished2023-06-05 18:09:21.355857
Duration14.89 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

Unnamed: 0
Real number (ℝ)

Distinct74530
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23383.64923
Minimum0
Maximum74529
Zeros18
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:21.745944image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1208
Q17165
median18155
Q336150
95-th percentile62364.5
Maximum74529
Range74529
Interquartile range (IQR)28985

Descriptive statistics

Standard deviation19147.53503
Coefficient of variation (CV)0.8188428949
Kurtosis-0.3880399155
Mean23383.64923
Median Absolute Deviation (MAD)12873
Skewness0.7785424136
Sum9460346352
Variance366628097.6
MonotonicityNot monotonic
2023-06-05T15:09:22.187187image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18
 
< 0.1%
24 18
 
< 0.1%
26 18
 
< 0.1%
27 18
 
< 0.1%
28 18
 
< 0.1%
29 18
 
< 0.1%
30 18
 
< 0.1%
31 18
 
< 0.1%
32 18
 
< 0.1%
33 18
 
< 0.1%
Other values (74520) 404391
> 99.9%
ValueCountFrequency (%)
0 18
< 0.1%
1 18
< 0.1%
2 18
< 0.1%
3 18
< 0.1%
4 18
< 0.1%
ValueCountFrequency (%)
74529 1
< 0.1%
74528 1
< 0.1%
74527 1
< 0.1%
74526 1
< 0.1%
74525 1
< 0.1%

id
Real number (ℝ)

Distinct74530
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23383.64923
Minimum0
Maximum74529
Zeros18
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:22.603871image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1208
Q17165
median18155
Q336150
95-th percentile62364.5
Maximum74529
Range74529
Interquartile range (IQR)28985

Descriptive statistics

Standard deviation19147.53503
Coefficient of variation (CV)0.8188428949
Kurtosis-0.3880399155
Mean23383.64923
Median Absolute Deviation (MAD)12873
Skewness0.7785424136
Sum9460346352
Variance366628097.6
MonotonicityNot monotonic
2023-06-05T15:09:22.927156image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18
 
< 0.1%
24 18
 
< 0.1%
26 18
 
< 0.1%
27 18
 
< 0.1%
28 18
 
< 0.1%
29 18
 
< 0.1%
30 18
 
< 0.1%
31 18
 
< 0.1%
32 18
 
< 0.1%
33 18
 
< 0.1%
Other values (74520) 404391
> 99.9%
ValueCountFrequency (%)
0 18
< 0.1%
1 18
< 0.1%
2 18
< 0.1%
3 18
< 0.1%
4 18
< 0.1%
ValueCountFrequency (%)
74529 1
< 0.1%
74528 1
< 0.1%
74527 1
< 0.1%
74526 1
< 0.1%
74525 1
< 0.1%

expiration_id
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0002842517135
Minimum0
Maximum1
Zeros404456
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:23.278350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01685739057
Coefficient of variation (CV)59.30444662
Kurtosis3513.052412
Mean0.0002842517135
Median Absolute Deviation (MAD)0
Skewness59.28773098
Sum115
Variance0.0002841716169
MonotonicityNot monotonic
2023-06-05T15:09:23.628623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 404456
> 99.9%
1 115
 
< 0.1%
ValueCountFrequency (%)
0 404456
> 99.9%
1 115
 
< 0.1%
ValueCountFrequency (%)
1 115
 
< 0.1%
0 404456
> 99.9%

src_ip
Text

Distinct810
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:24.076424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length35
Median length9
Mean length9.866577189
Min length2

Characters and Unicode

Total characters3991731
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique340 ?
Unique (%)0.1%

Sample

1st rowfe80::69dd:e614:2b2:dfd0
2nd row::
3rd rowfe80::69dd:e614:2b2:dfd0
4th row0.0.0.0
5th row10.0.2.2
ValueCountFrequency (%)
10.0.2.15 311169
76.9%
192.168.1.191 81248
 
20.1%
10.0.0.46 5096
 
1.3%
10.0.0.34 1787
 
0.4%
147.32.83.53 853
 
0.2%
192.168.33.254 729
 
0.2%
192.168.1.254 650
 
0.2%
fe80::69dd:e614:2b2:dfd0 332
 
0.1%
192.168.1.147 87
 
< 0.1%
192.168.1.111 75
 
< 0.1%
Other values (800) 2545
 
0.6%
2023-06-05T15:09:24.788865image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1212342
30.4%
1 1047008
26.2%
0 645419
16.2%
2 401506
 
10.1%
5 315516
 
7.9%
9 165995
 
4.2%
6 90377
 
2.3%
8 85496
 
2.1%
4 11272
 
0.3%
3 7893
 
0.2%
Other values (8) 8907
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2773104
69.5%
Other Punctuation 1214580
30.4%
Lowercase Letter 4047
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1047008
37.8%
0 645419
23.3%
2 401506
 
14.5%
5 315516
 
11.4%
9 165995
 
6.0%
6 90377
 
3.3%
8 85496
 
3.1%
4 11272
 
0.4%
3 7893
 
0.3%
7 2622
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
d 1492
36.9%
f 950
23.5%
e 844
20.9%
b 476
 
11.8%
a 186
 
4.6%
c 99
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 1212342
99.8%
: 2238
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3987684
99.9%
Latin 4047
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1212342
30.4%
1 1047008
26.3%
0 645419
16.2%
2 401506
 
10.1%
5 315516
 
7.9%
9 165995
 
4.2%
6 90377
 
2.3%
8 85496
 
2.1%
4 11272
 
0.3%
3 7893
 
0.2%
Other values (2) 4860
 
0.1%
Latin
ValueCountFrequency (%)
d 1492
36.9%
f 950
23.5%
e 844
20.9%
b 476
 
11.8%
a 186
 
4.6%
c 99
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3991731
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1212342
30.4%
1 1047008
26.2%
0 645419
16.2%
2 401506
 
10.1%
5 315516
 
7.9%
9 165995
 
4.2%
6 90377
 
2.3%
8 85496
 
2.1%
4 11272
 
0.3%
3 7893
 
0.2%
Other values (8) 8907
 
0.2%
Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:25.103326image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters6877707
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row08:00:27:a3:83:43
2nd row08:00:27:a3:83:43
3rd row08:00:27:a3:83:43
4th row08:00:27:a3:83:43
5th row52:54:00:12:35:02
ValueCountFrequency (%)
08:00:27:a3:83:43 311523
77.0%
60:6c:66:cb:78:61 81248
 
20.1%
78:e4:00:6c:39:cd 6883
 
1.7%
00:13:33:b0:18:50 3381
 
0.8%
b8:ac:6f:6d:5a:f5 853
 
0.2%
38:72:c0:5e:6b:22 218
 
0.1%
d0:53:49:1b:0c:90 118
 
< 0.1%
2c:6e:85:56:dd:b7 85
 
< 0.1%
40:b8:9a:44:0e:0d 74
 
< 0.1%
08:00:27:e1:e3:8a 43
 
< 0.1%
Other values (7) 145
 
< 0.1%
2023-06-05T15:09:25.855323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 2022855
29.4%
0 1044227
15.2%
3 952075
13.8%
8 715885
 
10.4%
6 415296
 
6.0%
7 400203
 
5.8%
4 318982
 
4.6%
a 313409
 
4.6%
2 312430
 
4.5%
c 177590
 
2.6%
Other values (7) 204755
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4260419
61.9%
Other Punctuation 2022855
29.4%
Lowercase Letter 594433
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1044227
24.5%
3 952075
22.3%
8 715885
16.8%
6 415296
 
9.7%
7 400203
 
9.4%
4 318982
 
7.5%
2 312430
 
7.3%
1 88275
 
2.1%
9 7255
 
0.2%
5 5791
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
a 313409
52.7%
c 177590
29.9%
b 86027
 
14.5%
d 8278
 
1.4%
e 7377
 
1.2%
f 1752
 
0.3%
Other Punctuation
ValueCountFrequency (%)
: 2022855
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6283274
91.4%
Latin 594433
 
8.6%

Most frequent character per script

Common
ValueCountFrequency (%)
: 2022855
32.2%
0 1044227
16.6%
3 952075
15.2%
8 715885
 
11.4%
6 415296
 
6.6%
7 400203
 
6.4%
4 318982
 
5.1%
2 312430
 
5.0%
1 88275
 
1.4%
9 7255
 
0.1%
Latin
ValueCountFrequency (%)
a 313409
52.7%
c 177590
29.9%
b 86027
 
14.5%
d 8278
 
1.4%
e 7377
 
1.2%
f 1752
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6877707
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 2022855
29.4%
0 1044227
15.2%
3 952075
13.8%
8 715885
 
10.4%
6 415296
 
6.0%
7 400203
 
5.8%
4 318982
 
4.6%
a 313409
 
4.6%
2 312430
 
4.5%
c 177590
 
2.6%
Other values (7) 204755
 
3.0%
Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:26.208593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters3236568
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row08:00:27
2nd row08:00:27
3rd row08:00:27
4th row08:00:27
5th row52:54:00
ValueCountFrequency (%)
08:00:27 311566
77.0%
60:6c:66 81248
 
20.1%
78:e4:00 6883
 
1.7%
00:13:33 3381
 
0.8%
b8:ac:6f 853
 
0.2%
38:72:c0 218
 
0.1%
d0:53:49 118
 
< 0.1%
2c:6e:85 85
 
< 0.1%
40:b8:9a 74
 
< 0.1%
44:6d:57 42
 
< 0.1%
Other values (6) 103
 
< 0.1%
2023-06-05T15:09:26.938231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1037007
32.0%
: 809142
25.0%
6 325978
 
10.1%
8 319690
 
9.9%
7 318744
 
9.8%
2 311930
 
9.6%
c 82416
 
2.5%
3 10486
 
0.3%
4 7226
 
0.2%
e 6999
 
0.2%
Other values (7) 6950
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2335073
72.1%
Other Punctuation 809142
 
25.0%
Lowercase Letter 92353
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1037007
44.4%
6 325978
 
14.0%
8 319690
 
13.7%
7 318744
 
13.7%
2 311930
 
13.4%
3 10486
 
0.4%
4 7226
 
0.3%
1 3449
 
0.1%
5 371
 
< 0.1%
9 192
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
c 82416
89.2%
e 6999
 
7.6%
a 959
 
1.0%
b 927
 
1.0%
f 853
 
0.9%
d 199
 
0.2%
Other Punctuation
ValueCountFrequency (%)
: 809142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3144215
97.1%
Latin 92353
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1037007
33.0%
: 809142
25.7%
6 325978
 
10.4%
8 319690
 
10.2%
7 318744
 
10.1%
2 311930
 
9.9%
3 10486
 
0.3%
4 7226
 
0.2%
1 3449
 
0.1%
5 371
 
< 0.1%
Latin
ValueCountFrequency (%)
c 82416
89.2%
e 6999
 
7.6%
a 959
 
1.0%
b 927
 
1.0%
f 853
 
0.9%
d 199
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3236568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1037007
32.0%
: 809142
25.0%
6 325978
 
10.1%
8 319690
 
9.9%
7 318744
 
9.8%
2 311930
 
9.6%
c 82416
 
2.5%
3 10486
 
0.3%
4 7226
 
0.2%
e 6999
 
0.2%
Other values (7) 6950
 
0.2%

src_port
Real number (ℝ)

Distinct30884
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54115.22687
Minimum0
Maximum65535
Zeros402
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:27.430563image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile37992
Q150860
median55219
Q359646
95-th percentile64223
Maximum65535
Range65535
Interquartile range (IQR)8786

Descriptive statistics

Standard deviation8734.361129
Coefficient of variation (CV)0.1614030216
Kurtosis12.06693039
Mean54115.22687
Median Absolute Deviation (MAD)4391
Skewness-2.573274957
Sum2.189345145 × 1010
Variance76289064.33
MonotonicityNot monotonic
2023-06-05T15:09:27.793162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59370 2112
 
0.5%
80 1496
 
0.4%
53 729
 
0.2%
443 531
 
0.1%
0 402
 
0.1%
546 304
 
0.1%
137 62
 
< 0.1%
49210 50
 
< 0.1%
49328 47
 
< 0.1%
49260 46
 
< 0.1%
Other values (30874) 398792
98.6%
ValueCountFrequency (%)
0 402
 
0.1%
53 729
0.2%
67 18
 
< 0.1%
68 33
 
< 0.1%
80 1496
0.4%
ValueCountFrequency (%)
65535 11
< 0.1%
65534 15
< 0.1%
65533 10
< 0.1%
65532 12
< 0.1%
65531 16
< 0.1%

dst_ip
Text

Distinct11785
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:28.489577image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length35
Median length14
Mean length13.53449456
Min length7

Characters and Unicode

Total characters5475664
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2064 ?
Unique (%)0.5%

Sample

1st rowff02::16
2nd rowff02::1:ffb2:dfd0
3rd rowff02::2
4th row255.255.255.255
5th row10.0.2.15
ValueCountFrequency (%)
192.168.33.254 242131
59.8%
208.91.112.53 12944
 
3.2%
8.8.8.8 3776
 
0.9%
23.51.123.27 3411
 
0.8%
192.168.1.191 2731
 
0.7%
93.184.220.29 1390
 
0.3%
172.217.23.238 1276
 
0.3%
178.255.83.1 1136
 
0.3%
173.241.240.143 1030
 
0.3%
173.241.240.220 931
 
0.2%
Other values (11775) 133815
33.1%
2023-06-05T15:09:29.508903image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1212342
22.1%
1 864901
15.8%
2 782794
14.3%
3 624104
11.4%
5 382152
 
7.0%
4 355241
 
6.5%
8 352257
 
6.4%
9 349825
 
6.4%
6 329696
 
6.0%
0 113460
 
2.1%
Other values (8) 108892
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4260828
77.8%
Other Punctuation 1213680
 
22.2%
Lowercase Letter 1156
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 864901
20.3%
2 782794
18.4%
3 624104
14.6%
5 382152
9.0%
4 355241
8.3%
8 352257
8.3%
9 349825
8.2%
6 329696
 
7.7%
0 113460
 
2.7%
7 106398
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
f 973
84.2%
d 67
 
5.8%
b 62
 
5.4%
a 31
 
2.7%
c 17
 
1.5%
e 6
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 1212342
99.9%
: 1338
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 5474508
> 99.9%
Latin 1156
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1212342
22.1%
1 864901
15.8%
2 782794
14.3%
3 624104
11.4%
5 382152
 
7.0%
4 355241
 
6.5%
8 352257
 
6.4%
9 349825
 
6.4%
6 329696
 
6.0%
0 113460
 
2.1%
Other values (2) 107736
 
2.0%
Latin
ValueCountFrequency (%)
f 973
84.2%
d 67
 
5.8%
b 62
 
5.4%
a 31
 
2.7%
c 17
 
1.5%
e 6
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5475664
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1212342
22.1%
1 864901
15.8%
2 782794
14.3%
3 624104
11.4%
5 382152
 
7.0%
4 355241
 
6.5%
8 352257
 
6.4%
9 349825
 
6.4%
6 329696
 
6.0%
0 113460
 
2.1%
Other values (8) 108892
 
2.0%
Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:29.798382image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters6877707
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row33:33:00:00:00:16
2nd row33:33:ff:b2:df:d0
3rd row33:33:00:00:00:02
4th rowff:ff:ff:ff:ff:ff
5th row08:00:27:a3:83:43
ValueCountFrequency (%)
52:54:00:12:35:02 311076
76.9%
00:13:33:b0:18:50 81248
 
20.1%
38:72:c0:5e:6b:22 6881
 
1.7%
60:6c:66:cb:78:61 2731
 
0.7%
00:16:47:f6:2b:d2 853
 
0.2%
01:00:5e:7f:ff:fa 851
 
0.2%
33:33:00:01:00:02 304
 
0.1%
78:e4:00:6c:39:cd 219
 
0.1%
ff:ff:ff:ff:ff:ff 109
 
< 0.1%
33:33:00:01:00:03 42
 
< 0.1%
Other values (14) 257
 
0.1%
2023-06-05T15:09:30.547247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 2022855
29.4%
0 1275856
18.6%
5 1022335
14.9%
2 955988
13.9%
3 563846
 
8.2%
1 478529
 
7.0%
4 312212
 
4.5%
b 91779
 
1.3%
8 91181
 
1.3%
6 22576
 
0.3%
Other values (7) 40550
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4734370
68.8%
Other Punctuation 2022855
29.4%
Lowercase Letter 120482
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1275856
26.9%
5 1022335
21.6%
2 955988
20.2%
3 563846
11.9%
1 478529
 
10.1%
4 312212
 
6.6%
8 91181
 
1.9%
6 22576
 
0.5%
7 11596
 
0.2%
9 251
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
b 91779
76.2%
c 12883
 
10.7%
e 8043
 
6.7%
f 5743
 
4.8%
d 1137
 
0.9%
a 897
 
0.7%
Other Punctuation
ValueCountFrequency (%)
: 2022855
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6757225
98.2%
Latin 120482
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
: 2022855
29.9%
0 1275856
18.9%
5 1022335
15.1%
2 955988
14.1%
3 563846
 
8.3%
1 478529
 
7.1%
4 312212
 
4.6%
8 91181
 
1.3%
6 22576
 
0.3%
7 11596
 
0.2%
Latin
ValueCountFrequency (%)
b 91779
76.2%
c 12883
 
10.7%
e 8043
 
6.7%
f 5743
 
4.8%
d 1137
 
0.9%
a 897
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6877707
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 2022855
29.4%
0 1275856
18.6%
5 1022335
14.9%
2 955988
13.9%
3 563846
 
8.2%
1 478529
 
7.0%
4 312212
 
4.5%
b 91779
 
1.3%
8 91181
 
1.3%
6 22576
 
0.3%
Other values (7) 40550
 
0.6%
Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:30.772029image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters3236568
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row33:33:00
2nd row33:33:ff
3rd row33:33:00
4th rowff:ff:ff
5th row08:00:27
ValueCountFrequency (%)
52:54:00 311076
76.9%
00:13:33 81248
 
20.1%
38:72:c0 6881
 
1.7%
60:6c:66 2731
 
0.7%
01:00:5e 935
 
0.2%
00:16:47 853
 
0.2%
33:33:00 422
 
0.1%
78:e4:00 219
 
0.1%
ff:ff:ff 109
 
< 0.1%
08:00:27 34
 
< 0.1%
Other values (4) 63
 
< 0.1%
2023-06-05T15:09:31.430582image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 809142
25.0%
0 800161
24.7%
5 623130
19.3%
2 317991
 
9.8%
4 312148
 
9.6%
3 252385
 
7.8%
1 83066
 
2.6%
6 11837
 
0.4%
c 9642
 
0.3%
7 8000
 
0.2%
Other values (6) 9066
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2415882
74.6%
Other Punctuation 809142
 
25.0%
Lowercase Letter 11544
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 800161
33.1%
5 623130
25.8%
2 317991
 
13.2%
4 312148
 
12.9%
3 252385
 
10.4%
1 83066
 
3.4%
6 11837
 
0.5%
7 8000
 
0.3%
8 7162
 
0.3%
9 2
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
c 9642
83.5%
e 1154
 
10.0%
f 720
 
6.2%
d 26
 
0.2%
b 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 809142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3225024
99.6%
Latin 11544
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
: 809142
25.1%
0 800161
24.8%
5 623130
19.3%
2 317991
 
9.9%
4 312148
 
9.7%
3 252385
 
7.8%
1 83066
 
2.6%
6 11837
 
0.4%
7 8000
 
0.2%
8 7162
 
0.2%
Latin
ValueCountFrequency (%)
c 9642
83.5%
e 1154
 
10.0%
f 720
 
6.2%
d 26
 
0.2%
b 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3236568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 809142
25.0%
0 800161
24.7%
5 623130
19.3%
2 317991
 
9.8%
4 312148
 
9.6%
3 252385
 
7.8%
1 83066
 
2.6%
6 11837
 
0.4%
c 9642
 
0.3%
7 8000
 
0.2%
Other values (6) 9066
 
0.3%

dst_port
Real number (ℝ)

Distinct3395
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean677.7593649
Minimum0
Maximum65502
Zeros402
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:31.854624image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile53
Q153
median53
Q380
95-th percentile443
Maximum65502
Range65502
Interquartile range (IQR)27

Descriptive statistics

Standard deviation4980.907592
Coefficient of variation (CV)7.349079703
Kurtosis94.32535489
Mean677.7593649
Median Absolute Deviation (MAD)0
Skewness9.616413192
Sum274201784
Variance24809440.44
MonotonicityNot monotonic
2023-06-05T15:09:32.288756image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 259919
64.2%
443 70776
 
17.5%
80 66433
 
16.4%
1900 851
 
0.2%
0 402
 
0.1%
547 304
 
0.1%
54081 178
 
< 0.1%
6881 142
 
< 0.1%
51413 138
 
< 0.1%
5355 84
 
< 0.1%
Other values (3385) 5344
 
1.3%
ValueCountFrequency (%)
0 402
 
0.1%
7 1
 
< 0.1%
22 1
 
< 0.1%
53 259919
64.2%
67 33
 
< 0.1%
ValueCountFrequency (%)
65502 1
< 0.1%
65173 2
< 0.1%
65035 2
< 0.1%
64964 2
< 0.1%
64913 2
< 0.1%

protocol
Real number (ℝ)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.18426679
Minimum1
Maximum58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:32.588237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q16
median17
Q317
95-th percentile17
Maximum58
Range57
Interquartile range (IQR)11

Descriptive statistics

Standard deviation5.278939051
Coefficient of variation (CV)0.400396862
Kurtosis-0.6608469047
Mean13.18426679
Median Absolute Deviation (MAD)0
Skewness-0.5245858032
Sum5333972
Variance27.86719751
MonotonicityNot monotonic
2023-06-05T15:09:32.918238image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
17 264029
65.3%
6 140140
34.6%
1 309
 
0.1%
58 74
 
< 0.1%
2 19
 
< 0.1%
ValueCountFrequency (%)
1 309
 
0.1%
2 19
 
< 0.1%
6 140140
34.6%
17 264029
65.3%
58 74
 
< 0.1%
ValueCountFrequency (%)
58 74
 
< 0.1%
17 264029
65.3%
6 140140
34.6%
2 19
 
< 0.1%
1 309
 
0.1%

ip_version
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.002259183
Minimum4
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:33.283651image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4
Q14
median4
Q34
95-th percentile4
Maximum6
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06718090216
Coefficient of variation (CV)0.01678574502
Kurtosis880.2877361
Mean4.002259183
Median Absolute Deviation (MAD)0
Skewness29.70325545
Sum1619198
Variance0.004513273615
MonotonicityNot monotonic
2023-06-05T15:09:33.627916image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
4 404114
99.9%
6 457
 
0.1%
ValueCountFrequency (%)
4 404114
99.9%
6 457
 
0.1%
ValueCountFrequency (%)
6 457
 
0.1%
4 404114
99.9%

vlan_id
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:33.955633image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:09:34.126648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%

tunnel_id
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.483052418 × 10-5
Minimum0
Maximum3
Zeros404569
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:34.284266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3
Range3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.006670192095
Coefficient of variation (CV)449.7610477
Kurtosis202283
Mean1.483052418 × 10-5
Median Absolute Deviation (MAD)0
Skewness449.759936
Sum6
Variance4.449146258 × 10-5
MonotonicityNot monotonic
2023-06-05T15:09:34.499164image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 404569
> 99.9%
3 2
 
< 0.1%
ValueCountFrequency (%)
0 404569
> 99.9%
3 2
 
< 0.1%
ValueCountFrequency (%)
3 2
 
< 0.1%
0 404569
> 99.9%
Distinct363825
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.413396589 × 1011
Minimum7392
Maximum1.493732977 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:34.921153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum7392
5-th percentile720695.5
Q13551851
median7926695
Q314573584.5
95-th percentile1.493731409 × 1012
Maximum1.493732977 × 1012
Range1.493732969 × 1012
Interquartile range (IQR)11021733.5

Descriptive statistics

Standard deviation6.250333142 × 1011
Coefficient of variation (CV)1.831118353
Kurtosis-0.3437370881
Mean3.413396589 × 1011
Median Absolute Deviation (MAD)5116022
Skewness1.286071954
Sum1.380961272 × 1017
Variance3.906666439 × 1023
MonotonicityNot monotonic
2023-06-05T15:09:35.349105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.493730733 × 101228
 
< 0.1%
1.493730732 × 101228
 
< 0.1%
1.493729245 × 101227
 
< 0.1%
1.493731159 × 101226
 
< 0.1%
1.49373175 × 101226
 
< 0.1%
1.493730983 × 101224
 
< 0.1%
1.493731092 × 101223
 
< 0.1%
1.493729262 × 101223
 
< 0.1%
1.493730652 × 101223
 
< 0.1%
1.493729261 × 101222
 
< 0.1%
Other values (363815) 404321
99.9%
ValueCountFrequency (%)
7392 1
< 0.1%
8122 1
< 0.1%
13080 1
< 0.1%
13100 1
< 0.1%
13121 1
< 0.1%
ValueCountFrequency (%)
1.493732977 × 10121
< 0.1%
1.493732973 × 10121
< 0.1%
1.493732972 × 10121
< 0.1%
1.493732961 × 10121
< 0.1%
1.49373296 × 10121
< 0.1%
Distinct371747
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4133968 × 1011
Minimum13099
Maximum1.49373298 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:35.801328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum13099
5-th percentile733894
Q13573582
median7942800
Q314591577
95-th percentile1.493731424 × 1012
Maximum1.49373298 × 1012
Range1.493732967 × 1012
Interquartile range (IQR)11017995

Descriptive statistics

Standard deviation6.250333122 × 1011
Coefficient of variation (CV)1.831118234
Kurtosis-0.3437370878
Mean3.4133968 × 1011
Median Absolute Deviation (MAD)5118336
Skewness1.286071954
Sum1.380961357 × 1017
Variance3.906666413 × 1023
MonotonicityNot monotonic
2023-06-05T15:09:36.320937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.493728105 × 101221
 
< 0.1%
1.493728071 × 101217
 
< 0.1%
1.493728087 × 101216
 
< 0.1%
1.493731028 × 101215
 
< 0.1%
1.493728072 × 101214
 
< 0.1%
1.493727927 × 101214
 
< 0.1%
1.493730788 × 101212
 
< 0.1%
1.38731541 × 101212
 
< 0.1%
1.493730472 × 101212
 
< 0.1%
1.493727927 × 101212
 
< 0.1%
Other values (371737) 404426
> 99.9%
ValueCountFrequency (%)
13099 1
< 0.1%
13119 1
< 0.1%
13139 1
< 0.1%
13158 1
< 0.1%
14160 1
< 0.1%
ValueCountFrequency (%)
1.49373298 × 10121
< 0.1%
1.493732979 × 10121
< 0.1%
1.493732973 × 10121
< 0.1%
1.493732973 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%

bidirectional_duration_ms
Real number (ℝ)

Distinct60853
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21054.90697
Minimum0
Maximum1799996
Zeros2207
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:36.726441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q125
median60
Q35925
95-th percentile127545.5
Maximum1799996
Range1799996
Interquartile range (IQR)5900

Descriptive statistics

Standard deviation69043.92114
Coefficient of variation (CV)3.279231832
Kurtosis187.7207372
Mean21054.90697
Median Absolute Deviation (MAD)50
Skewness10.03186614
Sum8518204767
Variance4767063047
MonotonicityNot monotonic
2023-06-05T15:09:37.101381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25 6112
 
1.5%
24 6098
 
1.5%
23 6095
 
1.5%
26 5985
 
1.5%
27 5853
 
1.4%
22 5780
 
1.4%
21 5741
 
1.4%
28 5729
 
1.4%
29 5591
 
1.4%
20 5518
 
1.4%
Other values (60843) 346069
85.5%
ValueCountFrequency (%)
0 2207
0.5%
1 224
 
0.1%
2 48
 
< 0.1%
3 805
 
0.2%
4 1023
0.3%
ValueCountFrequency (%)
1799996 1
< 0.1%
1799972 1
< 0.1%
1799686 1
< 0.1%
1799574 1
< 0.1%
1799507 1
< 0.1%

bidirectional_packets
Real number (ℝ)

Distinct1768
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.73725007
Minimum1
Maximum392213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:37.508169image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median2
Q315
95-th percentile76
Maximum392213
Range392212
Interquartile range (IQR)13

Descriptive statistics

Standard deviation975.9729192
Coefficient of variation (CV)32.81987799
Kurtosis88796.09903
Mean29.73725007
Median Absolute Deviation (MAD)0
Skewness270.1217905
Sum12030829
Variance952523.139
MonotonicityNot monotonic
2023-06-05T15:09:37.966272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 223110
55.1%
4 34370
 
8.5%
7 13734
 
3.4%
6 7752
 
1.9%
33 4724
 
1.2%
14 3997
 
1.0%
21 3778
 
0.9%
24 3698
 
0.9%
18 3642
 
0.9%
22 3601
 
0.9%
Other values (1758) 102165
25.3%
ValueCountFrequency (%)
1 1782
 
0.4%
2 223110
55.1%
3 3512
 
0.9%
4 34370
 
8.5%
5 2208
 
0.5%
ValueCountFrequency (%)
392213 1
< 0.1%
275466 1
< 0.1%
184518 2
< 0.1%
124890 2
< 0.1%
110611 2
< 0.1%

bidirectional_bytes
Real number (ℝ)

Distinct41062
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19777.9664
Minimum54
Maximum424668890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:38.445306image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile180
Q1258
median408
Q32244
95-th percentile33307.5
Maximum424668890
Range424668836
Interquartile range (IQR)1986

Descriptive statistics

Standard deviation1012961.368
Coefficient of variation (CV)51.21665933
Kurtosis101909.6272
Mean19777.9664
Median Absolute Deviation (MAD)191
Skewness287.838145
Sum8001591646
Variance1.026090732 × 1012
MonotonicityNot monotonic
2023-06-05T15:09:38.955369image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
394 6812
 
1.7%
408 6429
 
1.6%
390 5950
 
1.5%
320 4443
 
1.1%
228 4203
 
1.0%
225 4142
 
1.0%
166 4089
 
1.0%
313 3766
 
0.9%
188 3608
 
0.9%
331 3536
 
0.9%
Other values (41052) 357593
88.4%
ValueCountFrequency (%)
54 5
 
< 0.1%
62 16
< 0.1%
66 6
 
< 0.1%
68 1
 
< 0.1%
69 2
 
< 0.1%
ValueCountFrequency (%)
424668890 1
< 0.1%
307383769 1
< 0.1%
148005382 2
< 0.1%
128190733 2
< 0.1%
110825666 2
< 0.1%

src2dst_first_seen_ms
Real number (ℝ)

Distinct363825
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.413396589 × 1011
Minimum7392
Maximum1.493732977 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:39.405354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum7392
5-th percentile720695.5
Q13551851
median7926695
Q314573584.5
95-th percentile1.493731409 × 1012
Maximum1.493732977 × 1012
Range1.493732969 × 1012
Interquartile range (IQR)11021733.5

Descriptive statistics

Standard deviation6.250333142 × 1011
Coefficient of variation (CV)1.831118353
Kurtosis-0.3437370881
Mean3.413396589 × 1011
Median Absolute Deviation (MAD)5116022
Skewness1.286071954
Sum1.380961272 × 1017
Variance3.906666439 × 1023
MonotonicityNot monotonic
2023-06-05T15:09:39.853972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.493730733 × 101228
 
< 0.1%
1.493730732 × 101228
 
< 0.1%
1.493729245 × 101227
 
< 0.1%
1.493731159 × 101226
 
< 0.1%
1.49373175 × 101226
 
< 0.1%
1.493730983 × 101224
 
< 0.1%
1.493731092 × 101223
 
< 0.1%
1.493729262 × 101223
 
< 0.1%
1.493730652 × 101223
 
< 0.1%
1.493729261 × 101222
 
< 0.1%
Other values (363815) 404321
99.9%
ValueCountFrequency (%)
7392 1
< 0.1%
8122 1
< 0.1%
13080 1
< 0.1%
13100 1
< 0.1%
13121 1
< 0.1%
ValueCountFrequency (%)
1.493732977 × 10121
< 0.1%
1.493732973 × 10121
< 0.1%
1.493732972 × 10121
< 0.1%
1.493732961 × 10121
< 0.1%
1.49373296 × 10121
< 0.1%

src2dst_last_seen_ms
Real number (ℝ)

Distinct378068
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.413396799 × 1011
Minimum13080
Maximum1.49373298 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:40.306030image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum13080
5-th percentile733788
Q13573554.5
median7942800
Q314591561.5
95-th percentile1.493731424 × 1012
Maximum1.49373298 × 1012
Range1.493732967 × 1012
Interquartile range (IQR)11018007

Descriptive statistics

Standard deviation6.250333121 × 1011
Coefficient of variation (CV)1.831118235
Kurtosis-0.3437370878
Mean3.413396799 × 1011
Median Absolute Deviation (MAD)5118351
Skewness1.286071954
Sum1.380961356 × 1017
Variance3.906666413 × 1023
MonotonicityNot monotonic
2023-06-05T15:09:40.700154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.49372988 × 101224
 
< 0.1%
1.493728105 × 101223
 
< 0.1%
1.493727967 × 101220
 
< 0.1%
1.493728803 × 101218
 
< 0.1%
1.49373094 × 101217
 
< 0.1%
1.49373094 × 101217
 
< 0.1%
1.493730737 × 101216
 
< 0.1%
1.387315073 × 101216
 
< 0.1%
1.493728087 × 101215
 
< 0.1%
1.493731028 × 101215
 
< 0.1%
Other values (378058) 404390
> 99.9%
ValueCountFrequency (%)
13080 1
< 0.1%
13100 1
< 0.1%
13121 1
< 0.1%
13139 1
< 0.1%
14160 1
< 0.1%
ValueCountFrequency (%)
1.49373298 × 10121
< 0.1%
1.493732979 × 10121
< 0.1%
1.493732973 × 10121
< 0.1%
1.493732973 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%

src2dst_duration_ms
Real number (ℝ)

Distinct60719
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20980.71083
Minimum0
Maximum1799996
Zeros249230
Zeros (%)61.6%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:41.153731image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35882
95-th percentile127542.5
Maximum1799996
Range1799996
Interquartile range (IQR)5882

Descriptive statistics

Standard deviation69054.79629
Coefficient of variation (CV)3.291346839
Kurtosis187.6253696
Mean20980.71083
Median Absolute Deviation (MAD)0
Skewness10.02889317
Sum8488187163
Variance4768564890
MonotonicityNot monotonic
2023-06-05T15:09:41.599926image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 249230
61.6%
1 996
 
0.2%
102 83
 
< 0.1%
122 65
 
< 0.1%
103 64
 
< 0.1%
513 63
 
< 0.1%
512 59
 
< 0.1%
615 58
 
< 0.1%
1065 58
 
< 0.1%
1060 57
 
< 0.1%
Other values (60709) 153838
38.0%
ValueCountFrequency (%)
0 249230
61.6%
1 996
 
0.2%
2 36
 
< 0.1%
3 55
 
< 0.1%
4 46
 
< 0.1%
ValueCountFrequency (%)
1799996 1
< 0.1%
1799972 1
< 0.1%
1799684 1
< 0.1%
1799574 1
< 0.1%
1799507 1
< 0.1%

src2dst_packets
Real number (ℝ)

Distinct806
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.45363855
Minimum1
Maximum271835
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:42.015416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q38
95-th percentile32
Maximum271835
Range271834
Interquartile range (IQR)7

Descriptive statistics

Standard deviation534.1533309
Coefficient of variation (CV)46.63612605
Kurtosis175735.0527
Mean11.45363855
Median Absolute Deviation (MAD)0
Skewness383.4434809
Sum4633810
Variance285319.781
MonotonicityNot monotonic
2023-06-05T15:09:42.458823image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 223923
55.3%
2 37659
 
9.3%
4 21632
 
5.3%
10 8877
 
2.2%
17 8259
 
2.0%
11 7359
 
1.8%
8 7106
 
1.8%
9 6325
 
1.6%
7 6011
 
1.5%
12 5576
 
1.4%
Other values (796) 71844
 
17.8%
ValueCountFrequency (%)
1 223923
55.3%
2 37659
 
9.3%
3 3334
 
0.8%
4 21632
 
5.3%
5 3130
 
0.8%
ValueCountFrequency (%)
271835 1
< 0.1%
97615 2
< 0.1%
91724 2
< 0.1%
37225 1
< 0.1%
36078 2
< 0.1%

src2dst_bytes
Real number (ℝ)

Distinct14964
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3572.876266
Minimum54
Maximum383809522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:42.897306image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile72
Q180
median91
Q3984
95-th percentile4552.5
Maximum383809522
Range383809468
Interquartile range (IQR)904

Descriptive statistics

Standard deviation729417.4877
Coefficient of variation (CV)204.1541417
Kurtosis200119.2272
Mean3572.876266
Median Absolute Deviation (MAD)19
Skewness417.4640014
Sum1445482124
Variance5.320498713 × 1011
MonotonicityNot monotonic
2023-06-05T15:09:43.348836image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75 15430
 
3.8%
82 13804
 
3.4%
76 13484
 
3.3%
84 12420
 
3.1%
80 12338
 
3.0%
83 11954
 
3.0%
78 11108
 
2.7%
86 10452
 
2.6%
72 10111
 
2.5%
87 10015
 
2.5%
Other values (14954) 283455
70.1%
ValueCountFrequency (%)
54 8
 
< 0.1%
62 16
 
< 0.1%
64 224
 
0.1%
65 94
 
< 0.1%
66 665
0.2%
ValueCountFrequency (%)
383809522 1
< 0.1%
146054307 2
< 0.1%
111505374 2
< 0.1%
12644847 2
< 0.1%
5898809 1
< 0.1%

dst2src_first_seen_ms
Real number (ℝ)

Distinct359336
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.289295513 × 1011
Minimum0
Maximum1.493732961 × 1012
Zeros4514
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:43.798873image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile530639.5
Q13415493
median7708827
Q314150112
95-th percentile1.493731392 × 1012
Maximum1.493732961 × 1012
Range1.493732961 × 1012
Interquartile range (IQR)10734619

Descriptive statistics

Standard deviation6.172309094 × 1011
Coefficient of variation (CV)1.876483603
Kurtosis-0.1904624945
Mean3.289295513 × 1011
Median Absolute Deviation (MAD)5051409
Skewness1.344473205
Sum1.330753575 × 1017
Variance3.809739955 × 1023
MonotonicityNot monotonic
2023-06-05T15:09:44.092023image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4514
 
1.1%
9849460 14
 
< 0.1%
1.493728184 × 101213
 
< 0.1%
1.49373113 × 101212
 
< 0.1%
1.493730924 × 101212
 
< 0.1%
1.493729117 × 101212
 
< 0.1%
1.493729386 × 101212
 
< 0.1%
756205 11
 
< 0.1%
10348770 11
 
< 0.1%
1.493731485 × 101211
 
< 0.1%
Other values (359326) 399949
98.9%
ValueCountFrequency (%)
0 4514
1.1%
12401 1
 
< 0.1%
13099 1
 
< 0.1%
13119 1
 
< 0.1%
13139 1
 
< 0.1%
ValueCountFrequency (%)
1.493732961 × 10121
< 0.1%
1.49373296 × 10122
< 0.1%
1.49373296 × 10121
< 0.1%
1.49373296 × 10121
< 0.1%
1.49373296 × 10121
< 0.1%

dst2src_last_seen_ms
Real number (ℝ)

Distinct367107
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.289295719 × 1011
Minimum0
Maximum1.493732969 × 1012
Zeros4514
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:44.374906image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile557971
Q13431459.5
median7727368
Q314170702
95-th percentile1.493731405 × 1012
Maximum1.493732969 × 1012
Range1.493732969 × 1012
Interquartile range (IQR)10739242.5

Descriptive statistics

Standard deviation6.172309075 × 1011
Coefficient of variation (CV)1.876483479
Kurtosis-0.1904624941
Mean3.289295719 × 1011
Median Absolute Deviation (MAD)5054081
Skewness1.344473205
Sum1.330753658 × 1017
Variance3.809739932 × 1023
MonotonicityNot monotonic
2023-06-05T15:09:44.626499image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4514
 
1.1%
1.493731028 × 101215
 
< 0.1%
1.493730472 × 101212
 
< 0.1%
1.3873157 × 101210
 
< 0.1%
6917536 10
 
< 0.1%
1.493731296 × 101210
 
< 0.1%
1.493728797 × 10129
 
< 0.1%
1.493731049 × 10129
 
< 0.1%
1.493727074 × 10129
 
< 0.1%
13569002 9
 
< 0.1%
Other values (367097) 399964
98.9%
ValueCountFrequency (%)
0 4514
1.1%
13099 1
 
< 0.1%
13119 1
 
< 0.1%
13139 1
 
< 0.1%
13158 1
 
< 0.1%
ValueCountFrequency (%)
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732969 × 10122
< 0.1%
1.493732969 × 10121
< 0.1%
1.493732969 × 10121
< 0.1%

dst2src_duration_ms
Real number (ℝ)

Distinct59612
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20634.33134
Minimum0
Maximum1799314
Zeros241966
Zeros (%)59.8%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:45.087314image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35648
95-th percentile127183
Maximum1799314
Range1799314
Interquartile range (IQR)5648

Descriptive statistics

Standard deviation68277.36499
Coefficient of variation (CV)3.308920646
Kurtosis187.6492193
Mean20634.33134
Median Absolute Deviation (MAD)0
Skewness9.977041339
Sum8348052064
Variance4661798570
MonotonicityNot monotonic
2023-06-05T15:09:45.678189image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 241966
59.8%
1 5439
 
1.3%
2 1710
 
0.4%
3 1122
 
0.3%
4 826
 
0.2%
5 614
 
0.2%
6 536
 
0.1%
9 479
 
0.1%
8 473
 
0.1%
10 469
 
0.1%
Other values (59602) 150937
37.3%
ValueCountFrequency (%)
0 241966
59.8%
1 5439
 
1.3%
2 1710
 
0.4%
3 1122
 
0.3%
4 826
 
0.2%
ValueCountFrequency (%)
1799314 1
< 0.1%
1799261 1
< 0.1%
1798352 1
< 0.1%
1798350 1
< 0.1%
1798310 1
< 0.1%

dst2src_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct1481
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.28361153
Minimum0
Maximum238241
Zeros4514
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:46.101851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q37
95-th percentile43
Maximum238241
Range238241
Interquartile range (IQR)6

Descriptive statistics

Standard deviation548.0557298
Coefficient of variation (CV)29.97524471
Kurtosis100849.2151
Mean18.28361153
Median Absolute Deviation (MAD)0
Skewness276.6955355
Sum7397019
Variance300365.083
MonotonicityNot monotonic
2023-06-05T15:09:46.544191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 226686
56.0%
2 41113
 
10.2%
3 15417
 
3.8%
9 6641
 
1.6%
7 6337
 
1.6%
16 6146
 
1.5%
11 5430
 
1.3%
10 5166
 
1.3%
12 5135
 
1.3%
13 4872
 
1.2%
Other values (1471) 81628
 
20.2%
ValueCountFrequency (%)
0 4514
 
1.1%
1 226686
56.0%
2 41113
 
10.2%
3 15417
 
3.8%
4 4053
 
1.0%
ValueCountFrequency (%)
238241 1
< 0.1%
120378 1
< 0.1%
92794 2
< 0.1%
75240 1
< 0.1%
74533 2
< 0.1%

dst2src_bytes
Real number (ℝ)

SKEWED  ZEROS 

Distinct36589
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16205.09014
Minimum0
Maximum305372427
Zeros4514
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:46.903658image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile97
Q1166
median289
Q31012
95-th percentile27491.5
Maximum305372427
Range305372427
Interquartile range (IQR)846

Descriptive statistics

Standard deviation622403.8632
Coefficient of variation (CV)38.40792356
Kurtosis150427.6186
Mean16205.09014
Median Absolute Deviation (MAD)161
Skewness338.7406119
Sum6556109522
Variance3.87386569 × 1011
MonotonicityNot monotonic
2023-06-05T15:09:47.284149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
166 13464
 
3.3%
136 7671
 
1.9%
0 4514
 
1.1%
244 4500
 
1.1%
143 4425
 
1.1%
144 4087
 
1.0%
91 4069
 
1.0%
174 3736
 
0.9%
102 3275
 
0.8%
226 2793
 
0.7%
Other values (36579) 352037
87.0%
ValueCountFrequency (%)
0 4514
1.1%
54 367
 
0.1%
58 760
 
0.2%
62 1
 
< 0.1%
66 131
 
< 0.1%
ValueCountFrequency (%)
305372427 1
< 0.1%
108240611 2
< 0.1%
107191507 1
< 0.1%
57515689 1
< 0.1%
48622876 1
< 0.1%

bidirectional_min_ps
Real number (ℝ)

Distinct304
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.27199923
Minimum54
Maximum590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:47.710882image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile54
Q154
median75
Q383
95-th percentile93
Maximum590
Range536
Interquartile range (IQR)29

Descriptive statistics

Standard deviation22.534699
Coefficient of variation (CV)0.3034077341
Kurtosis124.0774562
Mean74.27199923
Median Absolute Deviation (MAD)9
Skewness8.326554214
Sum30048297
Variance507.8126588
MonotonicityNot monotonic
2023-06-05T15:09:48.076236image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54 102328
25.3%
66 37912
 
9.4%
75 18331
 
4.5%
76 16618
 
4.1%
80 15304
 
3.8%
82 15171
 
3.7%
84 14155
 
3.5%
78 13652
 
3.4%
83 13544
 
3.3%
72 12452
 
3.1%
Other values (294) 145104
35.9%
ValueCountFrequency (%)
54 102328
25.3%
56 1
 
< 0.1%
58 2
 
< 0.1%
62 397
 
0.1%
63 4
 
< 0.1%
ValueCountFrequency (%)
590 12
< 0.1%
553 6
< 0.1%
551 1
 
< 0.1%
549 4
 
< 0.1%
548 1
 
< 0.1%

bidirectional_mean_ps
Real number (ℝ)

Distinct86106
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean195.7435177
Minimum54
Maximum1350.138895
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:48.491748image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile68
Q1112.0769231
median157.5
Q3227.5
95-th percentile505.0084746
Maximum1350.138895
Range1296.138895
Interquartile range (IQR)115.4230769

Descriptive statistics

Standard deviation146.0739158
Coefficient of variation (CV)0.7462516127
Kurtosis9.620931425
Mean195.7435177
Median Absolute Deviation (MAD)52
Skewness2.788630851
Sum79192150.69
Variance21337.58886
MonotonicityNot monotonic
2023-06-05T15:09:48.936557image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56.28571429 6434
 
1.6%
68 6431
 
1.6%
55.71428571 5543
 
1.4%
160 4526
 
1.1%
114 4248
 
1.1%
112.5 4191
 
1.0%
83 4098
 
1.0%
156.5 3855
 
1.0%
94 3636
 
0.9%
165.5 3625
 
0.9%
Other values (86096) 357984
88.5%
ValueCountFrequency (%)
54 27
< 0.1%
54.5 48
< 0.1%
55.03581267 2
 
< 0.1%
55.04931507 1
 
< 0.1%
55.07417582 2
 
< 0.1%
ValueCountFrequency (%)
1350.138895 1
< 0.1%
1307.40428 1
< 0.1%
1305.295718 1
< 0.1%
1301.207532 1
< 0.1%
1298.695546 1
< 0.1%

bidirectional_stddev_ps
Real number (ℝ)

Distinct108910
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183.1591581
Minimum0
Maximum728.1035406
Zeros4519
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:49.353979image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q145.254834
median118.7939392
Q3249.9688011
95-th percentile622.3872637
Maximum728.1035406
Range728.1035406
Interquartile range (IQR)204.7139671

Descriptive statistics

Standard deviation184.7789496
Coefficient of variation (CV)1.008843628
Kurtosis0.7368078209
Mean183.1591581
Median Absolute Deviation (MAD)81.31727984
Skewness1.306582543
Sum74100883.76
Variance34143.26023
MonotonicityNot monotonic
2023-06-05T15:09:49.786298image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.3137085 25411
 
6.3%
43.13351365 8327
 
2.1%
19.79898987 7119
 
1.8%
4.535573676 6434
 
1.6%
3.346640106 6184
 
1.5%
3.14718317 5543
 
1.4%
98.28784258 5497
 
1.4%
187.383297 5390
 
1.3%
106.773124 4726
 
1.2%
0 4519
 
1.1%
Other values (108900) 325421
80.4%
ValueCountFrequency (%)
0 4519
1.1%
0.5006958946 40
 
< 0.1%
0.5007199428 2
 
< 0.1%
0.5007283325 2
 
< 0.1%
0.5007326011 1
 
< 0.1%
ValueCountFrequency (%)
728.1035406 1
< 0.1%
727.2549306 1
< 0.1%
723.849159 1
< 0.1%
723.6323307 1
< 0.1%
723.2549888 1
< 0.1%

bidirectional_max_ps
Real number (ℝ)

Distinct1454
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean515.7223553
Minimum54
Maximum1514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:50.220250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile74
Q1148
median273
Q3583
95-th percentile1514
Maximum1514
Range1460
Interquartile range (IQR)435

Descriptive statistics

Standard deviation514.4822876
Coefficient of variation (CV)0.9975954743
Kurtosis-0.3137959955
Mean515.7223553
Median Absolute Deviation (MAD)152
Skewness1.167030004
Sum208646309
Variance264692.0243
MonotonicityNot monotonic
2023-06-05T15:09:50.610372image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1474 46644
 
11.5%
1514 28844
 
7.1%
74 10047
 
2.5%
62 7126
 
1.8%
66 6702
 
1.7%
143 5541
 
1.4%
571 5164
 
1.3%
244 4752
 
1.2%
144 4160
 
1.0%
91 4082
 
1.0%
Other values (1444) 281509
69.6%
ValueCountFrequency (%)
54 27
 
< 0.1%
55 48
 
< 0.1%
62 7126
1.8%
63 4
 
< 0.1%
64 31
 
< 0.1%
ValueCountFrequency (%)
1514 28844
7.1%
1513 10
 
< 0.1%
1512 15
 
< 0.1%
1511 11
 
< 0.1%
1510 9
 
< 0.1%

src2dst_min_ps
Real number (ℝ)

Distinct309
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.42958096
Minimum54
Maximum590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:50.945072image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile54
Q166
median75
Q383
95-th percentile93
Maximum590
Range536
Interquartile range (IQR)17

Descriptive statistics

Standard deviation22.48017236
Coefficient of variation (CV)0.3020327681
Kurtosis125.3143241
Mean74.42958096
Median Absolute Deviation (MAD)9
Skewness8.398866795
Sum30112050
Variance505.3581495
MonotonicityNot monotonic
2023-06-05T15:09:51.344672image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54 97604
24.1%
66 42190
 
10.4%
75 18331
 
4.5%
76 16617
 
4.1%
80 15304
 
3.8%
82 15171
 
3.7%
84 14153
 
3.5%
78 13650
 
3.4%
83 13543
 
3.3%
72 12450
 
3.1%
Other values (299) 145558
36.0%
ValueCountFrequency (%)
54 97604
24.1%
55 48
 
< 0.1%
58 2
 
< 0.1%
62 400
 
0.1%
63 4
 
< 0.1%
ValueCountFrequency (%)
590 12
< 0.1%
553 6
< 0.1%
551 1
 
< 0.1%
549 4
 
< 0.1%
548 1
 
< 0.1%

src2dst_mean_ps
Real number (ℝ)

Distinct54043
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.97977858
Minimum54
Maximum1496.22811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:51.775414image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile68
Q176
median82.93103448
Q394
95-th percentile191.577381
Maximum1496.22811
Range1442.22811
Interquartile range (IQR)18

Descriptive statistics

Standard deviation65.53831094
Coefficient of variation (CV)0.655515664
Kurtosis81.38588928
Mean99.97977858
Median Absolute Deviation (MAD)7.931034483
Skewness6.995290844
Sum40448919
Variance4295.270202
MonotonicityNot monotonic
2023-06-05T15:09:52.205415image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75 17991
 
4.4%
76 16343
 
4.0%
80 15354
 
3.8%
82 15114
 
3.7%
84 14197
 
3.5%
83 13495
 
3.3%
78 13492
 
3.3%
77 12188
 
3.0%
72 12015
 
3.0%
81 11608
 
2.9%
Other values (54033) 262774
65.0%
ValueCountFrequency (%)
54 27
< 0.1%
54.03202149 1
 
< 0.1%
54.103558 1
 
< 0.1%
54.14763738 1
 
< 0.1%
54.28451883 1
 
< 0.1%
ValueCountFrequency (%)
1496.22811 2
< 0.1%
1482.564644 1
< 0.1%
1480.155116 1
< 0.1%
1478.520593 1
< 0.1%
1476.822064 1
< 0.1%

src2dst_stddev_ps
Real number (ℝ)

Distinct80656
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.27211691
Minimum0
Maximum1023.890619
Zeros259503
Zeros (%)64.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:52.648075image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q370.72513305
95-th percentile293.122403
Maximum1023.890619
Range1023.890619
Interquartile range (IQR)70.72513305

Descriptive statistics

Standard deviation113.600476
Coefficient of variation (CV)2.093164639
Kurtosis9.003822534
Mean54.27211691
Median Absolute Deviation (MAD)0
Skewness2.848622484
Sum21956924.61
Variance12905.06815
MonotonicityNot monotonic
2023-06-05T15:09:53.245087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 259503
64.1%
4 7316
 
1.8%
6 6435
 
1.6%
4 5544
 
1.4%
4.618802154 994
 
0.2%
5.656854249 951
 
0.2%
179.0171081 889
 
0.2%
2.828427125 697
 
0.2%
190.465845 679
 
0.2%
3.577708764 622
 
0.2%
Other values (80646) 120941
29.9%
ValueCountFrequency (%)
0 259503
64.1%
0.4472135955 1
 
< 0.1%
0.5 4
 
< 0.1%
0.5 2
 
< 0.1%
0.5477225575 1
 
< 0.1%
ValueCountFrequency (%)
1023.890619 1
< 0.1%
1018.233765 1
< 0.1%
795.3082421 1
< 0.1%
784.4513157 1
< 0.1%
757.9997361 1
< 0.1%

src2dst_max_ps
Real number (ℝ)

Distinct1431
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.9730307
Minimum54
Maximum1514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:53.676355image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile70
Q176
median84
Q3284
95-th percentile1060
Maximum1514
Range1460
Interquartile range (IQR)208

Descriptive statistics

Standard deviation338.7645445
Coefficient of variation (CV)1.355204374
Kurtosis5.297362423
Mean249.9730307
Median Absolute Deviation (MAD)10
Skewness2.375039036
Sum101131839
Variance114761.4166
MonotonicityNot monotonic
2023-06-05T15:09:54.104896image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74 21504
 
5.3%
75 17981
 
4.4%
76 16340
 
4.0%
80 15298
 
3.8%
82 15270
 
3.8%
84 14372
 
3.6%
83 13719
 
3.4%
78 13519
 
3.3%
1514 12565
 
3.1%
77 12172
 
3.0%
Other values (1421) 251831
62.2%
ValueCountFrequency (%)
54 27
 
< 0.1%
55 48
 
< 0.1%
62 7136
1.8%
63 4
 
< 0.1%
64 290
 
0.1%
ValueCountFrequency (%)
1514 12565
3.1%
1513 9
 
< 0.1%
1512 12
 
< 0.1%
1511 15
 
< 0.1%
1510 7
 
< 0.1%

dst2src_min_ps
Real number (ℝ)

Distinct496
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean164.3300484
Minimum0
Maximum1224
Zeros4514
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:54.446404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile54
Q166
median140
Q3235
95-th percentile417
Maximum1224
Range1224
Interquartile range (IQR)169

Descriptive statistics

Standard deviation119.6777878
Coefficient of variation (CV)0.7282769585
Kurtosis0.6997021525
Mean164.3300484
Median Absolute Deviation (MAD)86
Skewness1.132708021
Sum66483172
Variance14322.7729
MonotonicityNot monotonic
2023-06-05T15:09:54.879887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54 94914
23.5%
66 43539
 
10.8%
143 4890
 
1.2%
244 4781
 
1.2%
0 4514
 
1.1%
144 4298
 
1.1%
91 4147
 
1.0%
174 4136
 
1.0%
102 3426
 
0.8%
226 3174
 
0.8%
Other values (486) 232752
57.5%
ValueCountFrequency (%)
0 4514
 
1.1%
54 94914
23.5%
56 1
 
< 0.1%
58 763
 
0.2%
62 9
 
< 0.1%
ValueCountFrequency (%)
1224 1
 
< 0.1%
701 2
 
< 0.1%
683 1
 
< 0.1%
554 38
 
< 0.1%
553 376
0.1%

dst2src_mean_ps
Real number (ℝ)

Distinct68217
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean275.4100201
Minimum0
Maximum1512.885002
Zeros4514
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:55.288399image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile66
Q1133
median223
Q3347
95-th percentile753.355042
Maximum1512.885002
Range1512.885002
Interquartile range (IQR)214

Descriptive statistics

Standard deviation227.7754059
Coefficient of variation (CV)0.8270410998
Kurtosis6.462786572
Mean275.4100201
Median Absolute Deviation (MAD)101
Skewness2.287661016
Sum111422907.2
Variance51881.63553
MonotonicityNot monotonic
2023-06-05T15:09:55.717626image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55.33333333 12680
 
3.1%
68 7000
 
1.7%
244 4618
 
1.1%
0 4514
 
1.1%
143 4495
 
1.1%
144 4133
 
1.0%
91 4108
 
1.0%
174 3807
 
0.9%
102 3326
 
0.8%
226 2954
 
0.7%
Other values (68207) 352936
87.2%
ValueCountFrequency (%)
0 4514
1.1%
54 425
 
0.1%
54.02197802 2
 
< 0.1%
54.02209945 6
 
< 0.1%
54.11428571 1
 
< 0.1%
ValueCountFrequency (%)
1512.885002 1
< 0.1%
1509.840695 1
< 0.1%
1509.772182 1
< 0.1%
1509.61316 1
< 0.1%
1507.84294 1
< 0.1%

dst2src_stddev_ps
Real number (ℝ)

Distinct84789
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.8229101
Minimum0
Maximum1023.890619
Zeros234524
Zeros (%)58.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:56.161193image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3156.5059013
95-th percentile643.6279806
Maximum1023.890619
Range1023.890619
Interquartile range (IQR)156.5059013

Descriptive statistics

Standard deviation222.8853313
Coefficient of variation (CV)1.730168424
Kurtosis0.6516657409
Mean128.8229101
Median Absolute Deviation (MAD)0
Skewness1.510872767
Sum52118013.56
Variance49677.87092
MonotonicityNot monotonic
2023-06-05T15:09:56.602496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 234524
58.0%
2.309401077 12680
 
3.1%
2.828427125 7045
 
1.7%
8.485281374 5283
 
1.3%
66.46803743 1111
 
0.3%
72.12489168 893
 
0.2%
2.309401077 879
 
0.2%
16.97056275 851
 
0.2%
50.24384982 722
 
0.2%
195.1614716 688
 
0.2%
Other values (84779) 139895
34.6%
ValueCountFrequency (%)
0 234524
58.0%
0.2964997267 2
 
< 0.1%
0.2973176585 6
 
< 0.1%
0.5 1
 
< 0.1%
0.5773502692 1
 
< 0.1%
ValueCountFrequency (%)
1023.890619 1
 
< 0.1%
833.7033845 1
 
< 0.1%
818.6851247 3
< 0.1%
813.2525233 1
 
< 0.1%
810.2320655 1
 
< 0.1%

dst2src_max_ps
Real number (ℝ)

Distinct1447
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean485.7560527
Minimum0
Maximum1514
Zeros4514
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:57.027947image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile70
Q1146
median255
Q3517
95-th percentile1474
Maximum1514
Range1514
Interquartile range (IQR)371

Descriptive statistics

Standard deviation503.5485108
Coefficient of variation (CV)1.036628382
Kurtosis0.003600336548
Mean485.7560527
Median Absolute Deviation (MAD)135
Skewness1.291962847
Sum196522812
Variance253561.1028
MonotonicityNot monotonic
2023-06-05T15:09:57.458698image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1474 52537
 
13.0%
1514 18868
 
4.7%
58 13954
 
3.4%
70 9260
 
2.3%
244 4746
 
1.2%
143 4561
 
1.1%
0 4514
 
1.1%
144 4167
 
1.0%
91 4081
 
1.0%
174 3826
 
0.9%
Other values (1437) 284057
70.2%
ValueCountFrequency (%)
0 4514
 
1.1%
54 425
 
0.1%
58 13954
3.4%
60 3
 
< 0.1%
61 27
 
< 0.1%
ValueCountFrequency (%)
1514 18868
4.7%
1513 1
 
< 0.1%
1512 4
 
< 0.1%
1511 2
 
< 0.1%
1510 6
 
< 0.1%

bidirectional_min_piat_ms
Real number (ℝ)

SKEWED  ZEROS 

Distinct1514
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.37815365
Minimum0
Maximum116629
Zeros149584
Zeros (%)37.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:57.890349image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14
Q333
95-th percentile183
Maximum116629
Range116629
Interquartile range (IQR)33

Descriptive statistics

Standard deviation739.2943423
Coefficient of variation (CV)13.85012953
Kurtosis13094.63181
Mean53.37815365
Median Absolute Deviation (MAD)14
Skewness107.5716106
Sum21595253
Variance546556.1246
MonotonicityNot monotonic
2023-06-05T15:09:58.328565image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 149584
37.0%
1 16327
 
4.0%
25 6038
 
1.5%
24 5988
 
1.5%
23 5970
 
1.5%
26 5863
 
1.4%
27 5767
 
1.4%
22 5660
 
1.4%
28 5639
 
1.4%
21 5591
 
1.4%
Other values (1504) 192144
47.5%
ValueCountFrequency (%)
0 149584
37.0%
1 16327
 
4.0%
2 2908
 
0.7%
3 517
 
0.1%
4 235
 
0.1%
ValueCountFrequency (%)
116629 1
< 0.1%
116487 1
< 0.1%
101577 1
< 0.1%
99021 1
< 0.1%
96031 2
< 0.1%
Distinct124670
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean712.9321712
Minimum0
Maximum116629
Zeros2207
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:58.699834image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q123
median47
Q3404.3480769
95-th percentile3349.784091
Maximum116629
Range116629
Interquartile range (IQR)381.3480769

Descriptive statistics

Standard deviation2632.567056
Coefficient of variation (CV)3.692591192
Kurtosis180.5349984
Mean712.9321712
Median Absolute Deviation (MAD)35
Skewness11.00711498
Sum288431681.4
Variance6930409.304
MonotonicityNot monotonic
2023-06-05T15:09:59.145665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25 6002
 
1.5%
24 5923
 
1.5%
23 5902
 
1.5%
26 5796
 
1.4%
27 5683
 
1.4%
22 5609
 
1.4%
28 5574
 
1.4%
21 5560
 
1.4%
29 5405
 
1.3%
20 5360
 
1.3%
Other values (124660) 347757
86.0%
ValueCountFrequency (%)
0 2207
0.5%
0.3333333333 2
 
< 0.1%
0.6666666667 1
 
< 0.1%
0.6891447368 1
 
< 0.1%
0.8315789474 1
 
< 0.1%
ValueCountFrequency (%)
116629 1
< 0.1%
116487 1
< 0.1%
101577 1
< 0.1%
99021 1
< 0.1%
96031 2
< 0.1%
Distinct154890
Distinct (%)38.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1367.509644
Minimum0
Maximum80981.40412
Zeros224911
Zeros (%)55.6%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:09:59.582699image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31020.601505
95-th percentile4825.843661
Maximum80981.40412
Range80981.40412
Interquartile range (IQR)1020.601505

Descriptive statistics

Standard deviation4647.503367
Coefficient of variation (CV)3.398515972
Kurtosis87.07804966
Mean1367.509644
Median Absolute Deviation (MAD)0
Skewness8.282134156
Sum553254744.2
Variance21599287.54
MonotonicityNot monotonic
2023-06-05T15:10:00.035424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 224911
55.6%
1.527525232 702
 
0.2%
1.732050808 427
 
0.1%
1 407
 
0.1%
2.081665999 393
 
0.1%
2.309401077 333
 
0.1%
2.886751346 259
 
0.1%
2.645751311 238
 
0.1%
3.464101615 236
 
0.1%
4.041451884 231
 
0.1%
Other values (154880) 176434
43.6%
ValueCountFrequency (%)
0 224911
55.6%
0.4472135955 2
 
< 0.1%
0.5477225575 3
 
< 0.1%
0.5477225575 2
 
< 0.1%
0.5477225575 22
 
< 0.1%
ValueCountFrequency (%)
80981.40412 1
< 0.1%
69261.53637 1
< 0.1%
69218.52499 1
< 0.1%
69213.905 1
< 0.1%
69212.50277 1
< 0.1%

bidirectional_max_piat_ms
Real number (ℝ)

Distinct23540
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4253.394942
Minimum0
Maximum119996
Zeros2207
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:00.613977image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q125
median59
Q34669
95-th percentile10189
Maximum119996
Range119996
Interquartile range (IQR)4644

Descriptive statistics

Standard deviation12180.13009
Coefficient of variation (CV)2.863625469
Kurtosis28.74700096
Mean4253.394942
Median Absolute Deviation (MAD)49
Skewness5.073315828
Sum1720800245
Variance148355568.9
MonotonicityNot monotonic
2023-06-05T15:10:01.064707image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25 6131
 
1.5%
23 6100
 
1.5%
24 6085
 
1.5%
26 5988
 
1.5%
27 5840
 
1.4%
22 5796
 
1.4%
21 5769
 
1.4%
28 5755
 
1.4%
29 5568
 
1.4%
20 5512
 
1.4%
Other values (23530) 346027
85.5%
ValueCountFrequency (%)
0 2207
0.5%
1 225
 
0.1%
2 543
 
0.1%
3 1193
0.3%
4 947
0.2%
ValueCountFrequency (%)
119996 1
< 0.1%
119967 1
< 0.1%
119941 1
< 0.1%
119920 1
< 0.1%
119858 1
< 0.1%

src2dst_min_piat_ms
Real number (ℝ)

Distinct6566
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean630.0551251
Minimum0
Maximum120189
Zeros306451
Zeros (%)75.7%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:01.492761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile103
Maximum120189
Range120189
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6708.101205
Coefficient of variation (CV)10.64684809
Kurtosis180.1723121
Mean630.0551251
Median Absolute Deviation (MAD)0
Skewness12.9874325
Sum254902032
Variance44998621.77
MonotonicityNot monotonic
2023-06-05T15:10:01.938407image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 306451
75.7%
1 23627
 
5.8%
2 9745
 
2.4%
3 5708
 
1.4%
4 3369
 
0.8%
5 2244
 
0.6%
10 2109
 
0.5%
9 2006
 
0.5%
11 1948
 
0.5%
8 1887
 
0.5%
Other values (6556) 45477
 
11.2%
ValueCountFrequency (%)
0 306451
75.7%
1 23627
 
5.8%
2 9745
 
2.4%
3 5708
 
1.4%
4 3369
 
0.8%
ValueCountFrequency (%)
120189 1
< 0.1%
120130 1
< 0.1%
120027 1
< 0.1%
119979 1
< 0.1%
119960 1
< 0.1%

src2dst_mean_piat_ms
Real number (ℝ)

Distinct110628
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1570.462701
Minimum0
Maximum120189
Zeros249230
Zeros (%)61.6%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:02.352208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3775.7207792
95-th percentile6894.058824
Maximum120189
Range120189
Interquartile range (IQR)775.7207792

Descriptive statistics

Standard deviation7094.676992
Coefficient of variation (CV)4.517571151
Kurtosis140.0580259
Mean1570.462701
Median Absolute Deviation (MAD)0
Skewness10.97597106
Sum635363665.5
Variance50334441.63
MonotonicityNot monotonic
2023-06-05T15:10:02.804847image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 249230
61.6%
1 996
 
0.2%
102 101
 
< 0.1%
123 97
 
< 0.1%
103 72
 
< 0.1%
122 64
 
< 0.1%
133 63
 
< 0.1%
1050 63
 
< 0.1%
3 58
 
< 0.1%
129 58
 
< 0.1%
Other values (110618) 153769
38.0%
ValueCountFrequency (%)
0 249230
61.6%
1 996
 
0.2%
1.645833333 1
 
< 0.1%
2 36
 
< 0.1%
2.205882353 1
 
< 0.1%
ValueCountFrequency (%)
120189 1
< 0.1%
120130 1
< 0.1%
120027 1
< 0.1%
119979 1
< 0.1%
119960 1
< 0.1%

src2dst_stddev_piat_ms
Real number (ℝ)

Distinct139645
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.957753
Minimum0
Maximum84151.36382
Zeros261625
Zeros (%)64.7%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:03.219651image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31122.460142
95-th percentile4903.684592
Maximum84151.36382
Range84151.36382
Interquartile range (IQR)1122.460142

Descriptive statistics

Standard deviation3786.143182
Coefficient of variation (CV)2.821357954
Kurtosis80.70860423
Mean1341.957753
Median Absolute Deviation (MAD)0
Skewness7.128149101
Sum542917190.2
Variance14334880.19
MonotonicityNot monotonic
2023-06-05T15:10:03.652277image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 261625
64.7%
0.7071067812 55
 
< 0.1%
3.535533906 45
 
< 0.1%
2.828427125 43
 
< 0.1%
8.485281374 41
 
< 0.1%
11.3137085 41
 
< 0.1%
1.414213562 40
 
< 0.1%
4.242640687 39
 
< 0.1%
6.363961031 38
 
< 0.1%
2.121320344 36
 
< 0.1%
Other values (139635) 142568
35.2%
ValueCountFrequency (%)
0 261625
64.7%
0.4472135955 2
 
< 0.1%
0.5477225575 3
 
< 0.1%
0.5477225575 2
 
< 0.1%
0.5477225575 22
 
< 0.1%
ValueCountFrequency (%)
84151.36382 1
< 0.1%
83972.4658 1
< 0.1%
83682.55202 1
< 0.1%
81963.57543 1
< 0.1%
81626.2855 1
< 0.1%

src2dst_max_piat_ms
Real number (ℝ)

Distinct24106
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4246.257396
Minimum0
Maximum131048
Zeros249230
Zeros (%)61.6%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:04.066122image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34694
95-th percentile10402
Maximum131048
Range131048
Interquartile range (IQR)4694

Descriptive statistics

Standard deviation12230.40249
Coefficient of variation (CV)2.880278171
Kurtosis28.4593637
Mean4246.257396
Median Absolute Deviation (MAD)0
Skewness5.039205003
Sum1717912601
Variance149582745
MonotonicityNot monotonic
2023-06-05T15:10:04.516162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 249230
61.6%
1 996
 
0.2%
10048 804
 
0.2%
10101 735
 
0.2%
10100 723
 
0.2%
10098 711
 
0.2%
10080 705
 
0.2%
10094 692
 
0.2%
10095 689
 
0.2%
10112 682
 
0.2%
Other values (24096) 148604
36.7%
ValueCountFrequency (%)
0 249230
61.6%
1 996
 
0.2%
2 36
 
< 0.1%
3 56
 
< 0.1%
4 47
 
< 0.1%
ValueCountFrequency (%)
131048 1
< 0.1%
121741 1
< 0.1%
120824 1
< 0.1%
120189 1
< 0.1%
120130 1
< 0.1%

dst2src_min_piat_ms
Real number (ℝ)

Distinct8477
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean677.4538091
Minimum0
Maximum188740
Zeros337620
Zeros (%)83.5%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:04.949813image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile121
Maximum188740
Range188740
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6795.709131
Coefficient of variation (CV)10.0312509
Kurtosis175.6028224
Mean677.4538091
Median Absolute Deviation (MAD)0
Skewness12.77996891
Sum274078165
Variance46181662.59
MonotonicityNot monotonic
2023-06-05T15:10:05.342549image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 337620
83.5%
1 9687
 
2.4%
2 3670
 
0.9%
3 2998
 
0.7%
4 2684
 
0.7%
5 2294
 
0.6%
6 2154
 
0.5%
7 1993
 
0.5%
8 1782
 
0.4%
9 1678
 
0.4%
Other values (8467) 38011
 
9.4%
ValueCountFrequency (%)
0 337620
83.5%
1 9687
 
2.4%
2 3670
 
0.9%
3 2998
 
0.7%
4 2684
 
0.7%
ValueCountFrequency (%)
188740 1
< 0.1%
120028 1
< 0.1%
120005 1
< 0.1%
119979 1
< 0.1%
119956 1
< 0.1%

dst2src_mean_piat_ms
Real number (ℝ)

Distinct108665
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1535.772121
Minimum0
Maximum188740
Zeros241966
Zeros (%)59.8%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:05.775045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3597.5916667
95-th percentile6742.576754
Maximum188740
Range188740
Interquartile range (IQR)597.5916667

Descriptive statistics

Standard deviation7131.225755
Coefficient of variation (CV)4.643413992
Kurtosis141.211372
Mean1535.772121
Median Absolute Deviation (MAD)0
Skewness11.04137085
Sum621328862.7
Variance50854380.76
MonotonicityNot monotonic
2023-06-05T15:10:06.207606image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 241966
59.8%
1 5439
 
1.3%
2 1710
 
0.4%
3 1125
 
0.3%
4 831
 
0.2%
5 621
 
0.2%
6 541
 
0.1%
9 484
 
0.1%
8 477
 
0.1%
10 475
 
0.1%
Other values (108655) 150902
37.3%
ValueCountFrequency (%)
0 241966
59.8%
0.9601226994 1
 
< 0.1%
1 5439
 
1.3%
1.298207664 1
 
< 0.1%
1.328769308 1
 
< 0.1%
ValueCountFrequency (%)
188740 1
< 0.1%
120028 1
< 0.1%
120005 1
< 0.1%
119979 1
< 0.1%
119956 1
< 0.1%

dst2src_stddev_piat_ms
Real number (ℝ)

Distinct123905
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1241.688018
Minimum0
Maximum84519.05934
Zeros272321
Zeros (%)67.3%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:06.647948image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3753.0980165
95-th percentile4923.599461
Maximum84519.05934
Range84519.05934
Interquartile range (IQR)753.0980165

Descriptive statistics

Standard deviation3532.787277
Coefficient of variation (CV)2.845148883
Kurtosis91.89636678
Mean1241.688018
Median Absolute Deviation (MAD)0
Skewness7.438652196
Sum502350963
Variance12480585.94
MonotonicityNot monotonic
2023-06-05T15:10:07.075969image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 272321
67.3%
4468.20775 15
 
< 0.1%
4089.198516 13
 
< 0.1%
103.2375901 12
 
< 0.1%
2.828427125 12
 
< 0.1%
4273.753385 12
 
< 0.1%
4183.950824 12
 
< 0.1%
4568.616913 11
 
< 0.1%
4135.160456 11
 
< 0.1%
4277.996026 11
 
< 0.1%
Other values (123895) 132141
32.7%
ValueCountFrequency (%)
0 272321
67.3%
0.5773502692 2
 
< 0.1%
0.7071067812 11
 
< 0.1%
1 3
 
< 0.1%
1.154700538 4
 
< 0.1%
ValueCountFrequency (%)
84519.05934 1
< 0.1%
83328.29152 1
< 0.1%
83229.29657 1
< 0.1%
82228.03337 1
< 0.1%
82172.17193 1
< 0.1%

dst2src_max_piat_ms
Real number (ℝ)

Distinct23720
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4153.091465
Minimum0
Maximum188740
Zeros241966
Zeros (%)59.8%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:07.498592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34560
95-th percentile10385
Maximum188740
Range188740
Interquartile range (IQR)4560

Descriptive statistics

Standard deviation12112.88966
Coefficient of variation (CV)2.91659593
Kurtosis29.35584782
Mean4153.091465
Median Absolute Deviation (MAD)0
Skewness5.11717204
Sum1680220367
Variance146722096
MonotonicityNot monotonic
2023-06-05T15:10:07.929423image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 241966
59.8%
1 5439
 
1.3%
2 1710
 
0.4%
3 1122
 
0.3%
4 831
 
0.2%
10100 813
 
0.2%
10101 809
 
0.2%
10102 792
 
0.2%
10097 760
 
0.2%
10095 743
 
0.2%
Other values (23710) 149586
37.0%
ValueCountFrequency (%)
0 241966
59.8%
1 5439
 
1.3%
2 1710
 
0.4%
3 1122
 
0.3%
4 831
 
0.2%
ValueCountFrequency (%)
188740 1
< 0.1%
121165 1
< 0.1%
120182 1
< 0.1%
120028 1
< 0.1%
120005 1
< 0.1%

bidirectional_syn_packets
Real number (ℝ)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7039926243
Minimum0
Maximum9
Zeros264599
Zeros (%)65.4%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:08.488093image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9871725178
Coefficient of variation (CV)1.402248381
Kurtosis-0.4732754811
Mean0.7039926243
Median Absolute Deviation (MAD)0
Skewness0.8466493474
Sum284815
Variance0.9745095798
MonotonicityNot monotonic
2023-06-05T15:10:08.832072image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 264599
65.4%
2 131479
32.5%
3 5012
 
1.2%
1 2572
 
0.6%
4 649
 
0.2%
7 102
 
< 0.1%
5 74
 
< 0.1%
6 52
 
< 0.1%
8 31
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
0 264599
65.4%
1 2572
 
0.6%
2 131479
32.5%
3 5012
 
1.2%
4 649
 
0.2%
ValueCountFrequency (%)
9 1
 
< 0.1%
8 31
 
< 0.1%
7 102
< 0.1%
6 52
< 0.1%
5 74
< 0.1%

bidirectional_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:09.181976image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:10:09.446920image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%

bidirectional_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:09.688080image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:10:09.839202image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%

bidirectional_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:10.020005image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:10:10.183596image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%

bidirectional_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct1760
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.75192735
Minimum0
Maximum392213
Zeros265051
Zeros (%)65.5%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:10.462810image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q314
95-th percentile75
Maximum392213
Range392213
Interquartile range (IQR)14

Descriptive statistics

Standard deviation885.423847
Coefficient of variation (CV)33.0975722
Kurtosis121768.6325
Mean26.75192735
Median Absolute Deviation (MAD)0
Skewness317.0454919
Sum10823054
Variance783975.3889
MonotonicityNot monotonic
2023-06-05T15:10:10.791351image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 265051
65.5%
6 13998
 
3.5%
5 6832
 
1.7%
13 4744
 
1.2%
32 4673
 
1.2%
20 4018
 
1.0%
21 3531
 
0.9%
15 3438
 
0.8%
23 3248
 
0.8%
22 3224
 
0.8%
Other values (1750) 91814
 
22.7%
ValueCountFrequency (%)
0 265051
65.5%
1 1299
 
0.3%
2 67
 
< 0.1%
3 266
 
0.1%
4 741
 
0.2%
ValueCountFrequency (%)
392213 1
< 0.1%
275465 1
< 0.1%
124890 2
< 0.1%
110611 2
< 0.1%
89524 1
< 0.1%

bidirectional_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct663
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.334141597
Minimum0
Maximum34903
Zeros288903
Zeros (%)71.4%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:11.054307image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile19
Maximum34903
Range34903
Interquartile range (IQR)3

Descriptive statistics

Standard deviation84.37458883
Coefficient of variation (CV)15.81783822
Kurtosis118957.3199
Mean5.334141597
Median Absolute Deviation (MAD)0
Skewness308.397628
Sum2158039
Variance7119.07124
MonotonicityNot monotonic
2023-06-05T15:10:11.399315image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 288903
71.4%
6 11228
 
2.8%
7 10904
 
2.7%
2 10564
 
2.6%
5 9850
 
2.4%
8 8479
 
2.1%
3 8438
 
2.1%
4 8364
 
2.1%
9 6235
 
1.5%
10 4781
 
1.2%
Other values (653) 36825
 
9.1%
ValueCountFrequency (%)
0 288903
71.4%
1 1094
 
0.3%
2 10564
 
2.6%
3 8438
 
2.1%
4 8364
 
2.1%
ValueCountFrequency (%)
34903 1
< 0.1%
31175 1
< 0.1%
8200 1
< 0.1%
7499 1
< 0.1%
5833 1
< 0.1%

bidirectional_rst_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct61
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1864122737
Minimum0
Maximum259
Zeros374384
Zeros (%)92.5%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:11.825648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum259
Range259
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.041599987
Coefficient of variation (CV)5.587614838
Kurtosis10775.75737
Mean0.1864122737
Median Absolute Deviation (MAD)0
Skewness59.96230729
Sum75417
Variance1.084930533
MonotonicityNot monotonic
2023-06-05T15:10:12.269518image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 374384
92.5%
3 15186
 
3.8%
1 10235
 
2.5%
2 2716
 
0.7%
4 1011
 
0.2%
5 540
 
0.1%
9 88
 
< 0.1%
7 81
 
< 0.1%
6 66
 
< 0.1%
10 65
 
< 0.1%
Other values (51) 199
 
< 0.1%
ValueCountFrequency (%)
0 374384
92.5%
1 10235
 
2.5%
2 2716
 
0.7%
3 15186
 
3.8%
4 1011
 
0.2%
ValueCountFrequency (%)
259 1
< 0.1%
108 1
< 0.1%
93 1
< 0.1%
91 1
< 0.1%
89 1
< 0.1%

bidirectional_fin_packets
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6762175242
Minimum0
Maximum11
Zeros268274
Zeros (%)66.3%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:12.677822image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile2
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9850700523
Coefficient of variation (CV)1.456735469
Kurtosis0.7636582665
Mean0.6762175242
Median Absolute Deviation (MAD)0
Skewness1.064777014
Sum273578
Variance0.970363008
MonotonicityNot monotonic
2023-06-05T15:10:13.033554image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 268274
66.3%
2 122157
30.2%
1 8185
 
2.0%
3 3955
 
1.0%
4 1348
 
0.3%
5 401
 
0.1%
6 115
 
< 0.1%
9 62
 
< 0.1%
8 41
 
< 0.1%
7 30
 
< 0.1%
Other values (2) 3
 
< 0.1%
ValueCountFrequency (%)
0 268274
66.3%
1 8185
 
2.0%
2 122157
30.2%
3 3955
 
1.0%
4 1348
 
0.3%
ValueCountFrequency (%)
11 1
 
< 0.1%
10 2
 
< 0.1%
9 62
< 0.1%
8 41
< 0.1%
7 30
< 0.1%

src2dst_syn_packets
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3603075851
Minimum0
Maximum7
Zeros264600
Zeros (%)65.4%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:13.436780image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.524110253
Coefficient of variation (CV)1.454618983
Kurtosis8.787994968
Mean0.3603075851
Median Absolute Deviation (MAD)0
Skewness1.641319556
Sum145770
Variance0.2746915573
MonotonicityNot monotonic
2023-06-05T15:10:13.779749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 264600
65.4%
1 135833
33.6%
2 3165
 
0.8%
3 730
 
0.2%
7 103
 
< 0.1%
5 56
 
< 0.1%
4 44
 
< 0.1%
6 40
 
< 0.1%
ValueCountFrequency (%)
0 264600
65.4%
1 135833
33.6%
2 3165
 
0.8%
3 730
 
0.2%
4 44
 
< 0.1%
ValueCountFrequency (%)
7 103
 
< 0.1%
6 40
 
< 0.1%
5 56
 
< 0.1%
4 44
 
< 0.1%
3 730
0.2%

src2dst_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:14.146320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:10:14.479789image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%

src2dst_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:14.826452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:10:15.166033image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%

src2dst_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:15.508728image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:10:15.838749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%

src2dst_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct800
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.690131028
Minimum0
Maximum271835
Zeros266380
Zeros (%)65.8%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:16.217962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile31
Maximum271835
Range271835
Interquartile range (IQR)7

Descriptive statistics

Standard deviation493.4181908
Coefficient of variation (CV)50.91966139
Kurtosis235464.679
Mean9.690131028
Median Absolute Deviation (MAD)0
Skewness454.7169798
Sum3920346
Variance243461.511
MonotonicityNot monotonic
2023-06-05T15:10:16.665776image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 266380
65.8%
3 20804
 
5.1%
9 9627
 
2.4%
6 8191
 
2.0%
16 8152
 
2.0%
7 6689
 
1.7%
8 6662
 
1.6%
10 6154
 
1.5%
11 5022
 
1.2%
17 3827
 
0.9%
Other values (790) 63063
 
15.6%
ValueCountFrequency (%)
0 266380
65.8%
1 236
 
0.1%
2 1371
 
0.3%
3 20804
 
5.1%
4 2390
 
0.6%
ValueCountFrequency (%)
271835 1
< 0.1%
97615 2
< 0.1%
37224 1
< 0.1%
36078 2
< 0.1%
14284 1
< 0.1%

src2dst_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct258
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.487083849
Minimum0
Maximum6653
Zeros289591
Zeros (%)71.6%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:17.091177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum6653
Range6653
Interquartile range (IQR)1

Descriptive statistics

Standard deviation15.20357277
Coefficient of variation (CV)10.22374951
Kurtosis97828.78631
Mean1.487083849
Median Absolute Deviation (MAD)0
Skewness255.1348783
Sum601631
Variance231.1486251
MonotonicityNot monotonic
2023-06-05T15:10:17.483637image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 289591
71.6%
3 30442
 
7.5%
1 27465
 
6.8%
4 17853
 
4.4%
2 9575
 
2.4%
5 6988
 
1.7%
6 4804
 
1.2%
7 3545
 
0.9%
9 2059
 
0.5%
8 1855
 
0.5%
Other values (248) 10394
 
2.6%
ValueCountFrequency (%)
0 289591
71.6%
1 27465
 
6.8%
2 9575
 
2.4%
3 30442
 
7.5%
4 17853
 
4.4%
ValueCountFrequency (%)
6653 1
< 0.1%
2818 2
< 0.1%
1932 1
< 0.1%
1575 1
< 0.1%
1414 1
< 0.1%

src2dst_rst_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct54
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1356177284
Minimum0
Maximum259
Zeros379516
Zeros (%)93.8%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:17.734724image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum259
Range259
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8662801872
Coefficient of variation (CV)6.38766183
Kurtosis20974.60512
Mean0.1356177284
Median Absolute Deviation (MAD)0
Skewness86.02218879
Sum54867
Variance0.7504413627
MonotonicityNot monotonic
2023-06-05T15:10:18.042683image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 379516
93.8%
2 11228
 
2.8%
1 7468
 
1.8%
3 4828
 
1.2%
4 882
 
0.2%
5 258
 
0.1%
6 74
 
< 0.1%
10 68
 
< 0.1%
9 54
 
< 0.1%
7 34
 
< 0.1%
Other values (44) 161
 
< 0.1%
ValueCountFrequency (%)
0 379516
93.8%
1 7468
 
1.8%
2 11228
 
2.8%
3 4828
 
1.2%
4 882
 
0.2%
ValueCountFrequency (%)
259 1
< 0.1%
108 1
< 0.1%
70 1
< 0.1%
55 1
< 0.1%
52 1
< 0.1%

src2dst_fin_packets
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3330490816
Minimum0
Maximum10
Zeros270708
Zeros (%)66.9%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:18.435915image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4770074958
Coefficient of variation (CV)1.432243841
Kurtosis-0.01856533562
Mean0.3330490816
Median Absolute Deviation (MAD)0
Skewness0.8446839549
Sum134742
Variance0.2275361511
MonotonicityNot monotonic
2023-06-05T15:10:18.800015image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 270708
66.9%
1 133093
32.9%
2 707
 
0.2%
3 42
 
< 0.1%
4 11
 
< 0.1%
5 5
 
< 0.1%
9 1
 
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
0 270708
66.9%
1 133093
32.9%
2 707
 
0.2%
3 42
 
< 0.1%
4 11
 
< 0.1%
ValueCountFrequency (%)
10 1
< 0.1%
9 1
< 0.1%
8 1
< 0.1%
7 1
< 0.1%
6 1
< 0.1%

dst2src_syn_packets
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3436850392
Minimum0
Maximum6
Zeros268137
Zeros (%)66.3%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:19.307416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4893843385
Coefficient of variation (CV)1.42393262
Kurtosis-0.5344079971
Mean0.3436850392
Median Absolute Deviation (MAD)0
Skewness0.8655549009
Sum139045
Variance0.2394970307
MonotonicityNot monotonic
2023-06-05T15:10:19.643350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 268137
66.3%
1 134010
33.1%
2 2250
 
0.6%
3 166
 
< 0.1%
4 5
 
< 0.1%
6 2
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
0 268137
66.3%
1 134010
33.1%
2 2250
 
0.6%
3 166
 
< 0.1%
4 5
 
< 0.1%
ValueCountFrequency (%)
6 2
 
< 0.1%
5 1
 
< 0.1%
4 5
 
< 0.1%
3 166
 
< 0.1%
2 2250
0.6%

dst2src_cwr_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:20.003592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:10:20.333874image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%

dst2src_ece_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:20.681106image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:10:21.011162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%

dst2src_urg_packets
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:21.354185image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:10:21.689792image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%

dst2src_ack_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct1481
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.06179632
Minimum0
Maximum238241
Zeros265099
Zeros (%)65.5%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:22.077121image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile43
Maximum238241
Range238241
Interquartile range (IQR)7

Descriptive statistics

Standard deviation507.774766
Coefficient of variation (CV)29.76092062
Kurtosis131358.118
Mean17.06179632
Median Absolute Deviation (MAD)0
Skewness317.761118
Sum6902708
Variance257835.213
MonotonicityNot monotonic
2023-06-05T15:10:22.462770image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 265099
65.5%
3 15069
 
3.7%
2 7268
 
1.8%
9 6582
 
1.6%
7 6253
 
1.5%
16 6156
 
1.5%
11 5371
 
1.3%
10 5147
 
1.3%
12 5078
 
1.3%
13 4874
 
1.2%
Other values (1471) 77674
 
19.2%
ValueCountFrequency (%)
0 265099
65.5%
1 1461
 
0.4%
2 7268
 
1.8%
3 15069
 
3.7%
4 3150
 
0.8%
ValueCountFrequency (%)
238241 1
< 0.1%
120378 1
< 0.1%
75240 1
< 0.1%
74533 2
< 0.1%
39095 1
< 0.1%

dst2src_psh_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct592
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.847057748
Minimum0
Maximum34899
Zeros290033
Zeros (%)71.7%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:22.803015image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile12
Maximum34899
Range34899
Interquartile range (IQR)1

Descriptive statistics

Standard deviation75.77053402
Coefficient of variation (CV)19.69571007
Kurtosis139051.937
Mean3.847057748
Median Absolute Deviation (MAD)0
Skewness334.7878987
Sum1556408
Variance5741.173825
MonotonicityNot monotonic
2023-06-05T15:10:23.179455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 290033
71.7%
2 20119
 
5.0%
3 16016
 
4.0%
4 14274
 
3.5%
1 13908
 
3.4%
5 9694
 
2.4%
6 6127
 
1.5%
7 3984
 
1.0%
8 3013
 
0.7%
9 2496
 
0.6%
Other values (582) 24907
 
6.2%
ValueCountFrequency (%)
0 290033
71.7%
1 13908
 
3.4%
2 20119
 
5.0%
3 16016
 
4.0%
4 14274
 
3.5%
ValueCountFrequency (%)
34899 1
< 0.1%
24522 1
< 0.1%
8129 1
< 0.1%
7494 1
< 0.1%
5778 1
< 0.1%

dst2src_rst_packets
Real number (ℝ)

SKEWED  ZEROS 

Distinct30
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05079454533
Minimum0
Maximum46
Zeros388555
Zeros (%)96.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:23.556351image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum46
Range46
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3488127671
Coefficient of variation (CV)6.867130414
Kurtosis3831.724982
Mean0.05079454533
Median Absolute Deviation (MAD)0
Skewness40.00271573
Sum20550
Variance0.1216703465
MonotonicityNot monotonic
2023-06-05T15:10:23.875202image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 388555
96.0%
1 13241
 
3.3%
2 1984
 
0.5%
3 544
 
0.1%
4 146
 
< 0.1%
5 34
 
< 0.1%
6 16
 
< 0.1%
9 6
 
< 0.1%
7 6
 
< 0.1%
17 4
 
< 0.1%
Other values (20) 35
 
< 0.1%
ValueCountFrequency (%)
0 388555
96.0%
1 13241
 
3.3%
2 1984
 
0.5%
3 544
 
0.1%
4 146
 
< 0.1%
ValueCountFrequency (%)
46 1
< 0.1%
45 1
< 0.1%
44 1
< 0.1%
42 1
< 0.1%
36 1
< 0.1%

dst2src_fin_packets
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3431684426
Minimum0
Maximum8
Zeros274830
Zeros (%)67.9%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:24.243974image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5450872118
Coefficient of variation (CV)1.588395505
Kurtosis12.90305525
Mean0.3431684426
Median Absolute Deviation (MAD)0
Skewness2.177477503
Sum138836
Variance0.2971200685
MonotonicityNot monotonic
2023-06-05T15:10:24.602049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 274830
67.9%
1 123849
30.6%
2 3859
 
1.0%
3 1382
 
0.3%
4 417
 
0.1%
5 116
 
< 0.1%
8 68
 
< 0.1%
7 31
 
< 0.1%
6 19
 
< 0.1%
ValueCountFrequency (%)
0 274830
67.9%
1 123849
30.6%
2 3859
 
1.0%
3 1382
 
0.3%
4 417
 
0.1%
ValueCountFrequency (%)
8 68
 
< 0.1%
7 31
 
< 0.1%
6 19
 
< 0.1%
5 116
 
< 0.1%
4 417
0.1%
Distinct191
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:25.114018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length21
Median length3
Mean length5.708120454
Min length3

Characters and Unicode

Total characters2309340
Distinct characters54
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)< 0.1%

Sample

1st rowICMPV6
2nd rowICMPV6
3rd rowICMPV6
4th rowDHCP
5th rowDHCP
ValueCountFrequency (%)
dns 166574
41.2%
http 58206
 
14.4%
tls 54586
 
13.5%
dns.google 35537
 
8.8%
dns.facebook 18999
 
4.7%
dns.amazonaws 16988
 
4.2%
tls.google 5075
 
1.3%
http.ocsp 4437
 
1.1%
dns.twitter 4088
 
1.0%
dns.googleservices 2901
 
0.7%
Other values (181) 37180
 
9.2%
2023-06-05T15:10:26.045128image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 364394
15.8%
D 262332
11.4%
N 261585
11.3%
T 219155
 
9.5%
o 178604
 
7.7%
. 120600
 
5.2%
e 96256
 
4.2%
P 77210
 
3.3%
L 73040
 
3.2%
H 68319
 
3.0%
Other values (44) 587845
25.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1488736
64.5%
Lowercase Letter 698420
30.2%
Other Punctuation 120600
 
5.2%
Decimal Number 1132
 
< 0.1%
Open Punctuation 158
 
< 0.1%
Close Punctuation 158
 
< 0.1%
Connector Punctuation 136
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 178604
25.6%
e 96256
13.8%
l 52560
 
7.5%
a 52518
 
7.5%
g 48631
 
7.0%
n 31680
 
4.5%
c 28532
 
4.1%
b 25763
 
3.7%
t 25528
 
3.7%
m 24148
 
3.5%
Other values (14) 134200
19.2%
Uppercase Letter
ValueCountFrequency (%)
S 364394
24.5%
D 262332
17.6%
N 261585
17.6%
T 219155
14.7%
P 77210
 
5.2%
L 73040
 
4.9%
H 68319
 
4.6%
G 48325
 
3.2%
A 43756
 
2.9%
F 20284
 
1.4%
Other values (12) 50336
 
3.4%
Decimal Number
ValueCountFrequency (%)
6 626
55.3%
3 247
 
21.8%
5 247
 
21.8%
1 12
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 120600
100.0%
Open Punctuation
ValueCountFrequency (%)
( 158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 158
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2187156
94.7%
Common 122184
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 364394
16.7%
D 262332
12.0%
N 261585
12.0%
T 219155
10.0%
o 178604
 
8.2%
e 96256
 
4.4%
P 77210
 
3.5%
L 73040
 
3.3%
H 68319
 
3.1%
l 52560
 
2.4%
Other values (36) 533701
24.4%
Common
ValueCountFrequency (%)
. 120600
98.7%
6 626
 
0.5%
3 247
 
0.2%
5 247
 
0.2%
( 158
 
0.1%
) 158
 
0.1%
_ 136
 
0.1%
1 12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2309340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 364394
15.8%
D 262332
11.4%
N 261585
11.3%
T 219155
 
9.5%
o 178604
 
7.7%
. 120600
 
5.2%
e 96256
 
4.2%
P 77210
 
3.3%
L 73040
 
3.2%
H 68319
 
3.0%
Other values (44) 587845
25.5%
Distinct22
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:26.436081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length13
Median length7
Mean length6.174955694
Min length3

Characters and Unicode

Total characters2498208
Distinct characters36
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNetwork
2nd rowNetwork
3rd rowNetwork
4th rowNetwork
5th rowNetwork
ValueCountFrequency (%)
network 265689
65.7%
web 109800
27.1%
advertisement 14135
 
3.5%
socialnetwork 4319
 
1.1%
cloud 2977
 
0.7%
download 2614
 
0.6%
media 2037
 
0.5%
system 984
 
0.2%
conncheck 333
 
0.1%
unspecified 318
 
0.1%
Other values (12) 1365
 
0.3%
2023-06-05T15:10:26.948472image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 427021
17.1%
t 300083
12.0%
r 284829
11.4%
o 283658
11.4%
w 272622
10.9%
k 270341
10.8%
N 270025
10.8%
b 110100
 
4.4%
W 109800
 
4.4%
d 22193
 
0.9%
Other values (26) 147536
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2088819
83.6%
Uppercase Letter 409389
 
16.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 427021
20.4%
t 300083
14.4%
r 284829
13.6%
o 283658
13.6%
w 272622
13.1%
k 270341
12.9%
b 110100
 
5.3%
d 22193
 
1.1%
i 22192
 
1.1%
n 18214
 
0.9%
Other values (12) 77566
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
N 270025
66.0%
W 109800
26.8%
A 14141
 
3.5%
S 5784
 
1.4%
C 4155
 
1.0%
D 2614
 
0.6%
M 2201
 
0.5%
U 318
 
0.1%
V 192
 
< 0.1%
P 80
 
< 0.1%
Other values (4) 79
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2498208
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 427021
17.1%
t 300083
12.0%
r 284829
11.4%
o 283658
11.4%
w 272622
10.9%
k 270341
10.8%
N 270025
10.8%
b 110100
 
4.4%
W 109800
 
4.4%
d 22193
 
0.9%
Other values (26) 147536
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2498208
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 427021
17.1%
t 300083
12.0%
r 284829
11.4%
o 283658
11.4%
w 272622
10.9%
k 270341
10.8%
N 270025
10.8%
b 110100
 
4.4%
W 109800
 
4.4%
d 22193
 
0.9%
Other values (26) 147536
 
5.9%

application_is_guessed
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06026877853
Minimum0
Maximum1
Zeros380188
Zeros (%)94.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:27.310271image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2379844383
Coefficient of variation (CV)3.948718459
Kurtosis11.65663188
Mean0.06026877853
Median Absolute Deviation (MAD)0
Skewness3.695480246
Sum24383
Variance0.05663659286
MonotonicityNot monotonic
2023-06-05T15:10:27.521384image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 380188
94.0%
1 24383
 
6.0%
ValueCountFrequency (%)
0 380188
94.0%
1 24383
 
6.0%
ValueCountFrequency (%)
1 24383
 
6.0%
0 380188
94.0%

application_confidence
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.695415638
Minimum0
Maximum6
Zeros318
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:27.711777image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median6
Q36
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.196435874
Coefficient of variation (CV)0.2100699844
Kurtosis11.58279656
Mean5.695415638
Median Absolute Deviation (MAD)0
Skewness-3.68230304
Sum2304200
Variance1.431458802
MonotonicityNot monotonic
2023-06-05T15:10:27.885911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 379843
93.9%
1 24171
 
6.0%
0 318
 
0.1%
4 200
 
< 0.1%
5 27
 
< 0.1%
3 12
 
< 0.1%
ValueCountFrequency (%)
0 318
 
0.1%
1 24171
6.0%
3 12
 
< 0.1%
4 200
 
< 0.1%
5 27
 
< 0.1%
ValueCountFrequency (%)
6 379843
93.9%
5 27
 
< 0.1%
4 200
 
< 0.1%
3 12
 
< 0.1%
1 24171
 
6.0%
Distinct16191
Distinct (%)4.3%
Missing29634
Missing (%)7.3%
Memory size3.1 MiB
2023-06-05T15:10:28.282406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length79
Median length70
Mean length20.39620256
Min length3

Characters and Unicode

Total characters7647291
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique917 ?
Unique (%)0.2%

Sample

1st rowtiny71
2nd rowtiny71
3rd rowwpad.lan
4th rowwpad
5th rowwpad
ValueCountFrequency (%)
www.facebook.com 4476
 
1.2%
e8218.dscb1.akamaiedge.net 4183
 
1.1%
star-mini.c10r.facebook.com 4065
 
1.1%
email.seznam.cz 3939
 
1.1%
www.google.com 2816
 
0.8%
detectportal.firefox.com 2727
 
0.7%
scontent.xx.fbcdn.net 2431
 
0.6%
d2tpbry8f62bv9.cloudfront.net 2336
 
0.6%
ib.adnxs.com 2062
 
0.5%
www.google-analytics.com 1992
 
0.5%
Other values (16179) 343910
91.7%
2023-06-05T15:10:29.297203image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 873244
 
11.4%
o 612188
 
8.0%
e 584397
 
7.6%
c 574778
 
7.5%
a 505589
 
6.6%
t 433510
 
5.7%
m 413162
 
5.4%
s 375624
 
4.9%
n 352190
 
4.6%
i 305507
 
4.0%
Other values (30) 2617102
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6275986
82.1%
Other Punctuation 874095
 
11.4%
Decimal Number 382967
 
5.0%
Dash Punctuation 114156
 
1.5%
Connector Punctuation 87
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 612188
 
9.8%
e 584397
 
9.3%
c 574778
 
9.2%
a 505589
 
8.1%
t 433510
 
6.9%
m 413162
 
6.6%
s 375624
 
6.0%
n 352190
 
5.6%
i 305507
 
4.9%
d 283540
 
4.5%
Other values (16) 1835501
29.2%
Decimal Number
ValueCountFrequency (%)
1 85528
22.3%
2 55021
14.4%
0 43849
11.4%
8 33029
 
8.6%
3 33000
 
8.6%
5 28013
 
7.3%
7 26707
 
7.0%
6 26213
 
6.8%
9 25974
 
6.8%
4 25633
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 873244
99.9%
: 851
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 114156
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6275986
82.1%
Common 1371305
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 612188
 
9.8%
e 584397
 
9.3%
c 574778
 
9.2%
a 505589
 
8.1%
t 433510
 
6.9%
m 413162
 
6.6%
s 375624
 
6.0%
n 352190
 
5.6%
i 305507
 
4.9%
d 283540
 
4.5%
Other values (16) 1835501
29.2%
Common
ValueCountFrequency (%)
. 873244
63.7%
- 114156
 
8.3%
1 85528
 
6.2%
2 55021
 
4.0%
0 43849
 
3.2%
8 33029
 
2.4%
3 33000
 
2.4%
5 28013
 
2.0%
7 26707
 
1.9%
6 26213
 
1.9%
Other values (4) 52545
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7647291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 873244
 
11.4%
o 612188
 
8.0%
e 584397
 
7.6%
c 574778
 
7.5%
a 505589
 
6.6%
t 433510
 
5.7%
m 413162
 
5.4%
s 375624
 
4.9%
n 352190
 
4.6%
i 305507
 
4.0%
Other values (30) 2617102
34.2%
Distinct15
Distinct (%)< 0.1%
Missing334965
Missing (%)82.8%
Memory size3.1 MiB
2023-06-05T15:10:29.733410image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length47
Median length32
Mean length32.00316065
Min length23

Characters and Unicode

Total characters2227612
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1,15,3,6,44,46,47,31,33,121,249,43
2nd row1,15,3,6,44,46,47,31,33,121,249,43,252
3rd row0ffee3ba8e615ad22535e7f771690a28
4th row0ffee3ba8e615ad22535e7f771690a28
5th row0ffee3ba8e615ad22535e7f771690a28
ValueCountFrequency (%)
0ffee3ba8e615ad22535e7f771690a28 34834
50.0%
1a5fe5677b0e4fbbc854e8908225637d 12597
 
18.1%
07b4162d4db57554961824a21c4a0fde 10070
 
14.5%
dda6c525431b3259dac349220160cdcb 7626
 
11.0%
61d0d709fe7ac199ef4b2c52bc8cef75 3038
 
4.4%
6b87ab76e189e2222a12ff9d643060cd 1164
 
1.7%
c5ec106b91c503167f57054ca38da945 170
 
0.2%
d7150af4514b868defb854db0f62a441 32
 
< 0.1%
9a35e493f961ac377f948690b5334a9c 26
 
< 0.1%
1,15,3,6,44,46,47,31,33,121,249,43,252 12
 
< 0.1%
Other values (5) 37
 
0.1%
2023-06-05T15:10:30.543652image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 215132
 
9.7%
2 202493
 
9.1%
e 198871
 
8.9%
7 174387
 
7.8%
a 158351
 
7.1%
f 151614
 
6.8%
0 139278
 
6.3%
6 138525
 
6.2%
1 137026
 
6.2%
8 123206
 
5.5%
Other values (7) 588729
26.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1417525
63.6%
Lowercase Letter 809679
36.3%
Other Punctuation 408
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 215132
15.2%
2 202493
14.3%
7 174387
12.3%
0 139278
9.8%
6 138525
9.8%
1 137026
9.7%
8 123206
8.7%
3 106922
7.5%
4 95795
6.8%
9 84761
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
e 198871
24.6%
a 158351
19.6%
f 151614
18.7%
d 116843
14.4%
b 116741
14.4%
c 67259
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 408
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1417933
63.7%
Latin 809679
36.3%

Most frequent character per script

Common
ValueCountFrequency (%)
5 215132
15.2%
2 202493
14.3%
7 174387
12.3%
0 139278
9.8%
6 138525
9.8%
1 137026
9.7%
8 123206
8.7%
3 106922
7.5%
4 95795
6.8%
9 84761
 
6.0%
Latin
ValueCountFrequency (%)
e 198871
24.6%
a 158351
19.6%
f 151614
18.7%
d 116843
14.4%
b 116741
14.4%
c 67259
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2227612
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 215132
 
9.7%
2 202493
 
9.1%
e 198871
 
8.9%
7 174387
 
7.8%
a 158351
 
7.1%
f 151614
 
6.8%
0 139278
 
6.3%
6 138525
 
6.2%
1 137026
 
6.2%
8 123206
 
5.5%
Other values (7) 588729
26.4%
Distinct255
Distinct (%)0.4%
Missing335220
Missing (%)82.9%
Memory size3.1 MiB
2023-06-05T15:10:31.074501image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length32
Median length32
Mean length32
Min length32

Characters and Unicode

Total characters2219232
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)< 0.1%

Sample

1st row84480cf8cf0e732666092640e581e1a5
2nd row84480cf8cf0e732666092640e581e1a5
3rd row4fd467dd264720762ffe286277c00f57
4th row76cc3e2d3028143b23ec18e27dbd7ca9
5th row4fd467dd264720762ffe286277c00f57
ValueCountFrequency (%)
303951d4c50efb2e991652225a6f02b1 8927
 
12.9%
76cc3e2d3028143b23ec18e27dbd7ca9 5039
 
7.3%
2b33c1374db4ddf06942f92373c0b54b 3140
 
4.5%
fbe78c619e7ea20046131294ad087f05 2806
 
4.0%
410b9bedaf65dd26c6fe547154d60db4 2658
 
3.8%
7bee5c1d424b7e5f943b06983bb11422 2353
 
3.4%
d199ba0af2b08e204c73d6d81a1fd260 2201
 
3.2%
8d2a028aa94425f76ced7826b1f39039 2177
 
3.1%
ab41313cfec25328b20865eb1388e0a2 2095
 
3.0%
b898351eb5e266aefd3723d466935494 1993
 
2.9%
Other values (245) 35962
51.9%
2023-06-05T15:10:31.981088image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 187887
 
8.5%
1 163651
 
7.4%
3 149316
 
6.7%
b 148890
 
6.7%
5 147093
 
6.6%
0 144586
 
6.5%
e 142861
 
6.4%
d 142080
 
6.4%
9 141158
 
6.4%
4 132985
 
6.0%
Other values (6) 718725
32.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1426946
64.3%
Lowercase Letter 792286
35.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 187887
13.2%
1 163651
11.5%
3 149316
10.5%
5 147093
10.3%
0 144586
10.1%
9 141158
9.9%
4 132985
9.3%
6 129301
9.1%
7 118750
8.3%
8 112219
7.9%
Lowercase Letter
ValueCountFrequency (%)
b 148890
18.8%
e 142861
18.0%
d 142080
17.9%
f 124957
15.8%
c 120656
15.2%
a 112842
14.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1426946
64.3%
Latin 792286
35.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 187887
13.2%
1 163651
11.5%
3 149316
10.5%
5 147093
10.3%
0 144586
10.1%
9 141158
9.9%
4 132985
9.3%
6 129301
9.1%
7 118750
8.3%
8 112219
7.9%
Latin
ValueCountFrequency (%)
b 148890
18.8%
e 142861
18.0%
d 142080
17.9%
f 124957
15.8%
c 120656
15.2%
a 112842
14.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2219232
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 187887
 
8.5%
1 163651
 
7.4%
3 149316
 
6.7%
b 148890
 
6.7%
5 147093
 
6.6%
0 144586
 
6.5%
e 142861
 
6.4%
d 142080
 
6.4%
9 141158
 
6.4%
4 132985
 
6.0%
Other values (6) 718725
32.4%
Distinct11
Distinct (%)< 0.1%
Missing360975
Missing (%)89.2%
Memory size3.1 MiB
2023-06-05T15:10:32.424343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length151
Median length85
Mean length75.08553537
Min length6

Characters and Unicode

Total characters3273429
Distinct characters60
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowMicrosoft NCSI
2nd rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
3rd rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
4th rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
5th rowMozilla/5.0 (Windows NT 6.1; rv:53.0) Gecko/20100101 Firefox/53.0
ValueCountFrequency (%)
mozilla/5.0 43569
13.3%
gecko/20100101 43559
13.3%
linux 22031
 
6.7%
x11 22031
 
6.7%
x86_64 22021
 
6.7%
rv:43.0 22016
 
6.7%
firefox/43.0 22016
 
6.7%
iceweasel/43.0.4 22016
 
6.7%
windows 21540
 
6.6%
nt 21540
 
6.6%
Other values (38) 64777
19.8%
2023-06-05T15:10:33.268535image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 326982
 
10.0%
283520
 
8.7%
. 196351
 
6.0%
1 196305
 
6.0%
e 153244
 
4.7%
/ 152748
 
4.7%
o 152293
 
4.7%
i 130764
 
4.0%
4 110109
 
3.4%
l 109187
 
3.3%
Other values (50) 1461926
44.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1200216
36.7%
Decimal Number 960566
29.3%
Other Punctuation 458274
 
14.0%
Space Separator 283520
 
8.7%
Uppercase Letter 261664
 
8.0%
Close Punctuation 43581
 
1.3%
Open Punctuation 43581
 
1.3%
Connector Punctuation 22021
 
0.7%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 153244
12.8%
o 152293
12.7%
i 130764
10.9%
l 109187
9.1%
x 87611
 
7.3%
r 87167
 
7.3%
a 65619
 
5.5%
c 65616
 
5.5%
f 43586
 
3.6%
s 43580
 
3.6%
Other values (13) 261549
21.8%
Uppercase Letter
ValueCountFrequency (%)
M 43608
16.7%
G 43569
16.7%
F 43560
16.6%
L 22049
8.4%
I 22040
8.4%
X 22031
8.4%
T 21558
8.2%
N 21557
8.2%
W 21550
8.2%
C 41
 
< 0.1%
Other values (7) 101
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 326982
34.0%
1 196305
20.4%
4 110109
 
11.5%
3 107212
 
11.2%
5 86679
 
9.0%
6 65650
 
6.8%
2 45564
 
4.7%
8 22031
 
2.3%
7 30
 
< 0.1%
9 4
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 196351
42.8%
/ 152748
33.3%
; 65606
 
14.3%
: 43559
 
9.5%
, 10
 
< 0.1%
Space Separator
ValueCountFrequency (%)
283520
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43581
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43581
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 22021
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1811549
55.3%
Latin 1461880
44.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 153244
 
10.5%
o 152293
 
10.4%
i 130764
 
8.9%
l 109187
 
7.5%
x 87611
 
6.0%
r 87167
 
6.0%
a 65619
 
4.5%
c 65616
 
4.5%
M 43608
 
3.0%
f 43586
 
3.0%
Other values (30) 523185
35.8%
Common
ValueCountFrequency (%)
0 326982
18.0%
283520
15.7%
. 196351
10.8%
1 196305
10.8%
/ 152748
8.4%
4 110109
 
6.1%
3 107212
 
5.9%
5 86679
 
4.8%
6 65650
 
3.6%
; 65606
 
3.6%
Other values (10) 220387
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3273429
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 326982
 
10.0%
283520
 
8.7%
. 196351
 
6.0%
1 196305
 
6.0%
e 153244
 
4.7%
/ 152748
 
4.7%
o 152293
 
4.7%
i 130764
 
4.0%
4 110109
 
3.4%
l 109187
 
3.3%
Other values (50) 1461926
44.7%
Distinct75
Distinct (%)0.2%
Missing364804
Missing (%)90.2%
Memory size3.1 MiB
2023-06-05T15:10:33.696522image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length33
Median length26
Mean length14.62111801
Min length1

Characters and Unicode

Total characters581438
Distinct characters50
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)< 0.1%

Sample

1st rowtext/plain
2nd rowtext/plain
3rd rowapplication/ocsp-response
4th rowapplication/ocsp-response
5th rowapplication/ocsp-response
ValueCountFrequency (%)
image/gif 5871
14.8%
text/html 5709
14.4%
application/ocsp-response 4398
11.1%
application/javascript 4358
11.0%
image/jpeg 4081
10.3%
text/javascript 3809
9.6%
application/x-javascript 3084
7.8%
text/css 2152
 
5.4%
application/json 2030
 
5.1%
image/png 1579
 
4.0%
Other values (56) 2608
6.6%
2023-06-05T15:10:34.495738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 64795
11.1%
i 59296
 
10.2%
t 58765
 
10.1%
p 55956
 
9.6%
/ 39681
 
6.8%
e 38177
 
6.6%
c 32714
 
5.6%
s 31304
 
5.4%
o 27214
 
4.7%
n 24632
 
4.2%
Other values (40) 148904
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 532406
91.6%
Other Punctuation 39848
 
6.9%
Dash Punctuation 8337
 
1.4%
Decimal Number 444
 
0.1%
Math Symbol 160
 
< 0.1%
Uppercase Letter 149
 
< 0.1%
Space Separator 94
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 64795
12.2%
i 59296
11.1%
t 58765
11.0%
p 55956
10.5%
e 38177
 
7.2%
c 32714
 
6.1%
s 31304
 
5.9%
o 27214
 
5.1%
n 24632
 
4.6%
g 23526
 
4.4%
Other values (15) 116027
21.8%
Uppercase Letter
ValueCountFrequency (%)
P 25
16.8%
G 23
15.4%
J 21
14.1%
E 21
14.1%
T 14
9.4%
M 10
 
6.7%
L 10
 
6.7%
H 7
 
4.7%
U 6
 
4.0%
F 4
 
2.7%
Other values (4) 8
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/ 39681
99.6%
. 151
 
0.4%
* 11
 
< 0.1%
, 5
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 416
93.7%
4 25
 
5.6%
8 3
 
0.7%
Math Symbol
ValueCountFrequency (%)
+ 157
98.1%
= 3
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 8337
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 532555
91.6%
Common 48883
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 64795
12.2%
i 59296
11.1%
t 58765
11.0%
p 55956
10.5%
e 38177
 
7.2%
c 32714
 
6.1%
s 31304
 
5.9%
o 27214
 
5.1%
n 24632
 
4.6%
g 23526
 
4.4%
Other values (29) 116176
21.8%
Common
ValueCountFrequency (%)
/ 39681
81.2%
- 8337
 
17.1%
2 416
 
0.9%
+ 157
 
0.3%
. 151
 
0.3%
94
 
0.2%
4 25
 
0.1%
* 11
 
< 0.1%
, 5
 
< 0.1%
= 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 581438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 64795
11.1%
i 59296
 
10.2%
t 58765
 
10.1%
p 55956
 
9.6%
/ 39681
 
6.8%
e 38177
 
6.6%
c 32714
 
5.6%
s 31304
 
5.4%
o 27214
 
4.7%
n 24632
 
4.2%
Other values (40) 148904
25.6%

label
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros404571
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size3.1 MiB
2023-06-05T15:10:34.884931image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-05T15:10:35.212632image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%
ValueCountFrequency (%)
0 404571
100.0%